ITKImageProcessing Filter API =============================== This is the documentation for all filters included in the ITKImageProcessing module. These filters can be used by importing the appropriate module. Each filter is contained in the module: .. code:: python import itkimageprocessing # Instantiate and execute a filter from the module result = itkimageprocessing.SomeFilterName.execute(...) .. py:module:: ITKImageProcessing ITK Abs Image Filter -------------------- .. index:: pair: Filter Human Names; ITK Abs Image Filter .. index:: pair: Filter Class Names; ITKAbsImageFilter .. _ITKAbsImageFilter: .. py:class:: ITKAbsImageFilter itk::Math::abs() is used to perform the computation. `Link to the full online documentation for ITKAbsImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Acos Image Filter --------------------- .. index:: pair: Filter Human Names; ITK Acos Image Filter .. index:: pair: Filter Class Names; ITKAcosImageFilter .. _ITKAcosImageFilter: .. py:class:: ITKAcosImageFilter This filter is templated over the pixel type of the input image and the pixel type of the output image. `Link to the full online documentation for ITKAcosImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Adaptive Histogram Equalization Image Filter ------------------------------------------------ .. index:: pair: Filter Human Names; ITK Adaptive Histogram Equalization Image Filter .. index:: pair: Filter Class Names; ITKAdaptiveHistogramEqualizationImageFilter .. _ITKAdaptiveHistogramEqualizationImageFilter: .. py:class:: ITKAdaptiveHistogramEqualizationImageFilter Histogram equalization modifies the contrast in an image. The AdaptiveHistogramEqualizationImageFilter is a superset of many contrast enhancing filters. By modifying its parameters (alpha, beta, and window), the AdaptiveHistogramEqualizationImageFilter can produce an adaptively equalized histogram or a version of unsharp mask (local mean subtraction). Instead of applying a strict histogram equalization in a window about a pixel, this filter prescribes a mapping function (power law) controlled by the parameters alpha and beta. `Link to the full online documentation for ITKAdaptiveHistogramEqualizationImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Alpha | alpha | +------------------+---------------------------+ | Beta | beta | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Radius | radius | +------------------+---------------------------+ .. py:method:: Execute(data_structure, alpha, beta, input_image_data_path, input_image_geometry_path, output_array_name, radius) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float32Parameter alpha: Set/Get the value of alpha. Alpha = 0 produces the adaptive histogram equalization (provided beta=0). Alpha = 1 produces an unsharp mask. Default is 0.3. :param nx.Float32Parameter beta: Set/Get the value of beta. If beta = 1 (and alpha = 1), then the output image matches the input image. As beta approaches 0, the filter behaves as an unsharp mask. Default is 0.3. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.VectorUInt32Parameter radius: Radius Dimensions XYZ :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Approximate Signed Distance Map Image Filter ------------------------------------------------ .. index:: pair: Filter Human Names; ITK Approximate Signed Distance Map Image Filter .. index:: pair: Filter Class Names; ITKApproximateSignedDistanceMapImageFilter .. _ITKApproximateSignedDistanceMapImageFilter: .. py:class:: ITKApproximateSignedDistanceMapImageFilter The ApproximateSignedDistanceMapImageFilter takes as input a binary image and produces a signed distance map. Each pixel value in the output contains the approximate distance from that pixel to the nearest "object" in the binary image. This filter differs from the DanielssonDistanceMapImageFilter in that it calculates the distance to the "object edge" for pixels within the object. `Link to the full online documentation for ITKApproximateSignedDistanceMapImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Inside Value | inside_value | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ | Outside Value | outside_value | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, inside_value, output_array_name, outside_value) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.Float64Parameter inside_value: Set/Get intensity value representing the interior of objects in the mask. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.Float64Parameter outside_value: Set/Get intensity value representing non-objects in the mask. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Asin Image Filter --------------------- .. index:: pair: Filter Human Names; ITK Asin Image Filter .. index:: pair: Filter Class Names; ITKAsinImageFilter .. _ITKAsinImageFilter: .. py:class:: ITKAsinImageFilter This filter is templated over the pixel type of the input image and the pixel type of the output image. `Link to the full online documentation for ITKAsinImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Atan Image Filter --------------------- .. index:: pair: Filter Human Names; ITK Atan Image Filter .. index:: pair: Filter Class Names; ITKAtanImageFilter .. _ITKAtanImageFilter: .. py:class:: ITKAtanImageFilter This filter is templated over the pixel type of the input image and the pixel type of the output image. `Link to the full online documentation for ITKAtanImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Binary Contour Image Filter ------------------------------- .. index:: pair: Filter Human Names; ITK Binary Contour Image Filter .. index:: pair: Filter Class Names; ITKBinaryContourImageFilter .. _ITKBinaryContourImageFilter: .. py:class:: ITKBinaryContourImageFilter BinaryContourImageFilter takes a binary image as input, where the pixels in the objects are the pixels with a value equal to ForegroundValue. Only the pixels on the contours of the objects are kept. The pixels not on the border are changed to BackgroundValue. `Link to the full online documentation for ITKBinaryContourImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Background Value | background_value | +------------------+---------------------------+ | Foreground Value | foreground_value | +------------------+---------------------------+ | Fully Connected | fully_connected | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, background_value, foreground_value, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter background_value: Set/Get the background value used to mark the pixels not on the border of the objects. :param nx.Float64Parameter foreground_value: Set/Get the foreground value used to identify the objects in the input and output images. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Binary Dilate Image Filter ------------------------------ .. index:: pair: Filter Human Names; ITK Binary Dilate Image Filter .. index:: pair: Filter Class Names; ITKBinaryDilateImageFilter .. _ITKBinaryDilateImageFilter: .. py:class:: ITKBinaryDilateImageFilter BinaryDilateImageFilter is a binary dilation morphologic operation on the foreground of an image. Only the value designated by the intensity value "SetForegroundValue()" (alias as SetDilateValue() ) is considered as foreground, and other intensity values are considered background. `Link to the full online documentation for ITKBinaryDilateImageFilter `_ Mapping of UI display to python named argument +----------------------+---------------------------+ | UI Display | Python Named Argument | +======================+===========================+ | Background Value | background_value | +----------------------+---------------------------+ | BoundaryToForeground | boundary_to_foreground | +----------------------+---------------------------+ | Foreground Value | foreground_value | +----------------------+---------------------------+ | Input Cell Data | input_image_data_path | +----------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +----------------------+---------------------------+ | Kernel Radius | kernel_radius | +----------------------+---------------------------+ | Kernel Type | kernel_type_index | +----------------------+---------------------------+ | Output Cell Data | output_array_name | +----------------------+---------------------------+ .. py:method:: Execute(data_structure, background_value, boundary_to_foreground, foreground_value, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter background_value: Set/Get the background value used to mark the pixels not on the border of the objects. :param nx.BoolParameter boundary_to_foreground: Mark the boundary between foreground and background. :param nx.Float64Parameter foreground_value: Set/Get the foreground value used to identify the objects in the input and output images. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Binary Erode Image Filter ----------------------------- .. index:: pair: Filter Human Names; ITK Binary Erode Image Filter .. index:: pair: Filter Class Names; ITKBinaryErodeImageFilter .. _ITKBinaryErodeImageFilter: .. py:class:: ITKBinaryErodeImageFilter BinaryErodeImageFilter is a binary erosion morphologic operation on the foreground of an image. Only the value designated by the intensity value "SetForegroundValue()" (alias as SetErodeValue() ) is considered as foreground, and other intensity values are considered background. `Link to the full online documentation for ITKBinaryErodeImageFilter `_ Mapping of UI display to python named argument +----------------------+---------------------------+ | UI Display | Python Named Argument | +======================+===========================+ | Background Value | background_value | +----------------------+---------------------------+ | BoundaryToForeground | boundary_to_foreground | +----------------------+---------------------------+ | Foreground Value | foreground_value | +----------------------+---------------------------+ | Input Cell Data | input_image_data_path | +----------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +----------------------+---------------------------+ | Kernel Radius | kernel_radius | +----------------------+---------------------------+ | Kernel Type | kernel_type_index | +----------------------+---------------------------+ | Output Cell Data | output_array_name | +----------------------+---------------------------+ .. py:method:: Execute(data_structure, background_value, boundary_to_foreground, foreground_value, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter background_value: Set/Get the background value used to mark the pixels not on the border of the objects. :param nx.BoolParameter boundary_to_foreground: Mark the boundary between foreground and background. :param nx.Float64Parameter foreground_value: Set/Get the foreground value used to identify the objects in the input and output images. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Binary Morphological Closing Image Filter --------------------------------------------- .. index:: pair: Filter Human Names; ITK Binary Morphological Closing Image Filter .. index:: pair: Filter Class Names; ITKBinaryMorphologicalClosingImageFilter .. _ITKBinaryMorphologicalClosingImageFilter: .. py:class:: ITKBinaryMorphologicalClosingImageFilter This filter removes small (i.e., smaller than the structuring element) holes and tube like structures in the interior or at the boundaries of the image. The morphological closing of an image "f" is defined as: Closing(f) = Erosion(Dilation(f)). `Link to the full online documentation for ITKBinaryMorphologicalClosingImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Foreground Value | foreground_value | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Kernel Radius | kernel_radius | +------------------+---------------------------+ | Kernel Type | kernel_type_index | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Safe Border | safe_border | +------------------+---------------------------+ .. py:method:: Execute(data_structure, foreground_value, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, safe_border) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter foreground_value: Set the value in the image to consider as 'foreground'. Defaults to maximum value of InputPixelType. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.BoolParameter safe_border: A safe border is added to input image to avoid borders effects and remove it once the closing is done :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Binary Morphological Opening Image Filter --------------------------------------------- .. index:: pair: Filter Human Names; ITK Binary Morphological Opening Image Filter .. index:: pair: Filter Class Names; ITKBinaryMorphologicalOpeningImageFilter .. _ITKBinaryMorphologicalOpeningImageFilter: .. py:class:: ITKBinaryMorphologicalOpeningImageFilter This filter removes small (i.e., smaller than the structuring element) structures in the interior or at the boundaries of the image. The morphological opening of an image "f" is defined as: Opening(f) = Dilatation(Erosion(f)). `Link to the full online documentation for ITKBinaryMorphologicalOpeningImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Background Value | background_value | +------------------+---------------------------+ | Foreground Value | foreground_value | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Kernel Radius | kernel_radius | +------------------+---------------------------+ | Kernel Type | kernel_type_index | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, background_value, foreground_value, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter background_value: Set the value in eroded part of the image. Defaults to zero :param nx.Float64Parameter foreground_value: Set the value in the image to consider as 'foreground'. Defaults to maximum value of PixelType. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Binary Opening By Reconstruction Image Filter ------------------------------------------------- .. index:: pair: Filter Human Names; ITK Binary Opening By Reconstruction Image Filter .. index:: pair: Filter Class Names; ITKBinaryOpeningByReconstructionImageFilter .. _ITKBinaryOpeningByReconstructionImageFilter: .. py:class:: ITKBinaryOpeningByReconstructionImageFilter This filter removes small (i.e., smaller than the structuring element) objects in the image. It is defined as: Opening(f) = ReconstructionByDilatation(Erosion(f)). `Link to the full online documentation for ITKBinaryOpeningByReconstructionImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Background Value | background_value | +------------------+---------------------------+ | Foreground Value | foreground_value | +------------------+---------------------------+ | Fully Connected | fully_connected | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Kernel Radius | kernel_radius | +------------------+---------------------------+ | Kernel Type | kernel_type_index | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, background_value, foreground_value, fully_connected, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter background_value: Set the value in eroded part of the image. Defaults to zero :param nx.Float64Parameter foreground_value: Set the value in the image to consider as 'foreground'. Defaults to maximum value of PixelType. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Binary Projection Image Filter ---------------------------------- .. index:: pair: Filter Human Names; ITK Binary Projection Image Filter .. index:: pair: Filter Class Names; ITKBinaryProjectionImageFilter .. _ITKBinaryProjectionImageFilter: .. py:class:: ITKBinaryProjectionImageFilter Image projection is a very common task in image analysis to reduce the dimension of an image. A basefilter is provided with some specialized filters which implement different projection methods. `Link to the full online documentation for ITKBinaryProjectionImageFilter `_ Mapping of UI display to python named argument +-------------------------+----------------------------+ | UI Display | Python Named Argument | +=========================+============================+ | Background Value | background_value | +-------------------------+----------------------------+ | Foreground Value | foreground_value | +-------------------------+----------------------------+ | Input Cell Data | input_image_data_path | +-------------------------+----------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+----------------------------+ | Output Image Data Array | output_array_name | +-------------------------+----------------------------+ | Created Image Geometry | output_image_geometry_name | +-------------------------+----------------------------+ | Projection Dimension | projection_dimension | +-------------------------+----------------------------+ | Perform In-Place | remove_original_geometry | +-------------------------+----------------------------+ .. py:method:: Execute(data_structure, background_value, foreground_value, input_image_data_path, input_image_geometry_path, output_array_name, output_image_geometry_name, projection_dimension, remove_original_geometry) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter background_value: Set the value used as 'background'. Any pixel value which is not DilateValue is considered background. BackgroundValue is used for defining boundary conditions. Defaults to NumericTraits::NonpositiveMin() . :param nx.Float64Parameter foreground_value: Set the value in the image to consider as 'foreground'. Defaults to maximum value of PixelType. Subclasses may alias this to DilateValue or ErodeValue. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.StringParameter output_image_geometry_name: The name of the projected geometry :param nx.UInt32Parameter projection_dimension: The dimension index to project. 0=Slowest moving dimension. :param nx.BoolParameter remove_original_geometry: Performs the projection in-place for the given Image Geometry :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Binary Thinning Image Filter -------------------------------- .. index:: pair: Filter Human Names; ITK Binary Thinning Image Filter .. index:: pair: Filter Class Names; ITKBinaryThinningImageFilter .. _ITKBinaryThinningImageFilter: .. py:class:: ITKBinaryThinningImageFilter This class is parameterized over the type of the input image and the type of the output image. `Link to the full online documentation for ITKBinaryThinningImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Binary Threshold Image Filter --------------------------------- .. index:: pair: Filter Human Names; ITK Binary Threshold Image Filter .. index:: pair: Filter Class Names; ITKBinaryThresholdImageFilter .. _ITKBinaryThresholdImageFilter: .. py:class:: ITKBinaryThresholdImageFilter This filter produces an output image whose pixels are either one of two values ( OutsideValue or InsideValue ), depending on whether the corresponding input image pixels lie between the two thresholds ( LowerThreshold and UpperThreshold ). Values equal to either threshold is considered to be between the thresholds. `Link to the full online documentation for ITKBinaryThresholdImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Inside Value | inside_value | +------------------+---------------------------+ | Lower Threshold | lower_threshold | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Outside Value | outside_value | +------------------+---------------------------+ | Upper Threshold | upper_threshold | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, inside_value, lower_threshold, output_array_name, outside_value, upper_threshold) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.UInt8Parameter inside_value: Set the 'inside' pixel value. The default value NumericTraits::max() :param nx.Float64Parameter lower_threshold: The lower threshold that a pixel value could be and still be considered 'Inside Value' :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.UInt8Parameter outside_value: Set the 'outside' pixel value. The default value NumericTraits::ZeroValue() . :param nx.Float64Parameter upper_threshold: Set the thresholds. The default lower threshold is NumericTraits::NonpositiveMin() . The default upper threshold is NumericTraits::max . An exception is thrown if the lower threshold is greater than the upper threshold. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Black Top Hat Image Filter ------------------------------ .. index:: pair: Filter Human Names; ITK Black Top Hat Image Filter .. index:: pair: Filter Class Names; ITKBlackTopHatImageFilter .. _ITKBlackTopHatImageFilter: .. py:class:: ITKBlackTopHatImageFilter Black top hat extracts local minima that are smaller than the structuring element. It subtracts the background from the input image. The output of the filter transforms the black valleys into white peaks. `Link to the full online documentation for ITKBlackTopHatImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Kernel Radius | kernel_radius | +------------------+---------------------------+ | Kernel Type | kernel_type_index | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Safe Border | safe_border | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, safe_border) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.BoolParameter safe_border: A safe border is added to input image to avoid borders effects and remove it once the closing is done :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Closing By Reconstruction Image Filter ------------------------------------------ .. index:: pair: Filter Human Names; ITK Closing By Reconstruction Image Filter .. index:: pair: Filter Class Names; ITKClosingByReconstructionImageFilter .. _ITKClosingByReconstructionImageFilter: .. py:class:: ITKClosingByReconstructionImageFilter This filter is similar to the morphological closing, but contrary to the morphological closing, the closing by reconstruction preserves the shape of the components. The closing by reconstruction of an image "f" is defined as: `Link to the full online documentation for ITKClosingByReconstructionImageFilter `_ Mapping of UI display to python named argument +---------------------+---------------------------+ | UI Display | Python Named Argument | +=====================+===========================+ | Fully Connected | fully_connected | +---------------------+---------------------------+ | Input Cell Data | input_image_data_path | +---------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +---------------------+---------------------------+ | Kernel Radius | kernel_radius | +---------------------+---------------------------+ | Kernel Type | kernel_type_index | +---------------------+---------------------------+ | Output Cell Data | output_array_name | +---------------------+---------------------------+ | PreserveIntensities | preserve_intensities | +---------------------+---------------------------+ .. py:method:: Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, preserve_intensities) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.BoolParameter preserve_intensities: Set/Get whether the original intensities of the image retained for those pixels unaffected by the opening by reconstruction. If Off, the output pixel contrast will be reduced. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Connected Component Image Filter ------------------------------------ .. index:: pair: Filter Human Names; ITK Connected Component Image Filter .. index:: pair: Filter Class Names; ITKConnectedComponentImageFilter .. _ITKConnectedComponentImageFilter: .. py:class:: ITKConnectedComponentImageFilter ConnectedComponentImageFilter labels the objects in a binary image (non-zero pixels are considered to be objects, zero-valued pixels are considered to be background). Each distinct object is assigned a unique label. The filter experiments with some improvements to the existing implementation, and is based on run length encoding along raster lines. If the output background value is set to zero (the default), the final object labels start with 1 and are consecutive. If the output background is set to a non-zero value (by calling the SetBackgroundValue() routine of the filter), the final labels start at 0, and remain consecutive except for skipping the background value as needed. Objects that are reached earlier by a raster order scan have a lower label. This is different to the behaviour of the original connected component image filter which did not produce consecutive labels or impose any particular ordering. `Link to the full online documentation for ITKConnectedComponentImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Fully Connected | fully_connected | +-------------------------+---------------------------+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Cos Image Filter -------------------- .. index:: pair: Filter Human Names; ITK Cos Image Filter .. index:: pair: Filter Class Names; ITKCosImageFilter .. _ITKCosImageFilter: .. py:class:: ITKCosImageFilter This filter is templated over the pixel type of the input image and the pixel type of the output image. `Link to the full online documentation for ITKCosImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Curvature Anisotropic Diffusion Image Filter ------------------------------------------------ .. index:: pair: Filter Human Names; ITK Curvature Anisotropic Diffusion Image Filter .. index:: pair: Filter Class Names; ITKCurvatureAnisotropicDiffusionImageFilter .. _ITKCurvatureAnisotropicDiffusionImageFilter: .. py:class:: ITKCurvatureAnisotropicDiffusionImageFilter For detailed information on anisotropic diffusion and the MCDE see itkAnisotropicDiffusionFunction and itkCurvatureNDAnisotropicDiffusionFunction. `Link to the full online documentation for ITKCurvatureAnisotropicDiffusionImageFilter `_ Mapping of UI display to python named argument +-------------------------------------+-------------------------------------+ | UI Display | Python Named Argument | +=====================================+=====================================+ | Conductance Parameter | conductance_parameter | +-------------------------------------+-------------------------------------+ | Conductance Scaling Update Interval | conductance_scaling_update_interval | +-------------------------------------+-------------------------------------+ | Input Cell Data | input_image_data_path | +-------------------------------------+-------------------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------------------+-------------------------------------+ | Number Of Iterations | number_of_iterations | +-------------------------------------+-------------------------------------+ | Output Image Data Array | output_array_name | +-------------------------------------+-------------------------------------+ | Time Step | time_step | +-------------------------------------+-------------------------------------+ .. py:method:: Execute(data_structure, conductance_parameter, conductance_scaling_update_interval, input_image_data_path, input_image_geometry_path, number_of_iterations, output_array_name, time_step) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter conductance_parameter: The conductance parameter controls the sensitivity of the conductance term in the basic anisotropic diffusion equation :param nx.UInt32Parameter conductance_scaling_update_interval: The interval between conductance updates. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.UInt32Parameter number_of_iterations: Specifies the number of iterations (time-step updates) that the solver will perform to produce a solution image :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.Float64Parameter time_step: The time step to be used for each iteration. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Curvature Flow Image Filter ------------------------------- .. index:: pair: Filter Human Names; ITK Curvature Flow Image Filter .. index:: pair: Filter Class Names; ITKCurvatureFlowImageFilter .. _ITKCurvatureFlowImageFilter: .. py:class:: ITKCurvatureFlowImageFilter CurvatureFlowImageFilter implements a curvature driven image denoising algorithm. Iso-brightness contours in the grayscale input image are viewed as a level set. The level set is then evolved using a curvature-based speed function: `Link to the full online documentation for ITKCurvatureFlowImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Number Of Iterations | number_of_iterations | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ | Time Step | time_step | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, number_of_iterations, output_array_name, time_step) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.UInt32Parameter number_of_iterations: The number of update iterations :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.Float64Parameter time_step: The timestep between iteration updates :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Danielsson Distance Map Image Filter ---------------------------------------- .. index:: pair: Filter Human Names; ITK Danielsson Distance Map Image Filter .. index:: pair: Filter Class Names; ITKDanielssonDistanceMapImageFilter .. _ITKDanielssonDistanceMapImageFilter: .. py:class:: ITKDanielssonDistanceMapImageFilter The input is assumed to contain numeric codes defining objects. The filter will produce as output the following images: `Link to the full online documentation for ITKDanielssonDistanceMapImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Input Is Binary | input_is_binary | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ | Squared Distance | squared_distance | +-------------------------+---------------------------+ | Use Image Spacing | use_image_spacing | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, input_is_binary, output_array_name, squared_distance, use_image_spacing) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.BoolParameter input_is_binary: Set/Get if the input is binary. If this variable is set, each nonzero pixel in the input image will be given a unique numeric code to be used by the Voronoi partition. If the image is binary but you are not interested in the Voronoi regions of the different nonzero pixels, then you need not set this. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.BoolParameter squared_distance: Set/Get if the distance should be squared. :param nx.BoolParameter use_image_spacing: Set/Get if image spacing should be used in computing distances. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Dilate Object Morphology Image Filter ----------------------------------------- .. index:: pair: Filter Human Names; ITK Dilate Object Morphology Image Filter .. index:: pair: Filter Class Names; ITKDilateObjectMorphologyImageFilter .. _ITKDilateObjectMorphologyImageFilter: .. py:class:: ITKDilateObjectMorphologyImageFilter Dilate an image using binary morphology. Pixel values matching the object value are considered the "foreground" and all other pixels are "background". This is useful in processing mask images containing only one object. `Link to the full online documentation for ITKDilateObjectMorphologyImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Kernel Radius | kernel_radius | +------------------+---------------------------+ | Kernel Type | kernel_type_index | +------------------+---------------------------+ | Object Value | object_value | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, object_value, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.Float64Parameter object_value: The pixel value of the 'Object' to be dilated :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Discrete Gaussian Image Filter ---------------------------------- .. index:: pair: Filter Human Names; ITK Discrete Gaussian Image Filter .. index:: pair: Filter Class Names; ITKDiscreteGaussianImageFilter .. _ITKDiscreteGaussianImageFilter: .. py:class:: ITKDiscreteGaussianImageFilter The Gaussian operator used here was described by Tony Lindeberg (Discrete Scale-Space Theory and the Scale-Space Primal Sketch. Dissertation. Royal Institute of Technology, Stockholm, Sweden. May 1991.) The Gaussian kernel used here was designed so that smoothing and derivative operations commute after discretization. `Link to the full online documentation for ITKDiscreteGaussianImageFilter `_ Mapping of UI display to python named argument +--------------------+---------------------------+ | UI Display | Python Named Argument | +====================+===========================+ | Input Cell Data | input_image_data_path | +--------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +--------------------+---------------------------+ | MaximumError | maximum_error | +--------------------+---------------------------+ | MaximumKernelWidth | maximum_kernel_width | +--------------------+---------------------------+ | Output Cell Data | output_array_name | +--------------------+---------------------------+ | Use Image Spacing | use_image_spacing | +--------------------+---------------------------+ | Variance | variance | +--------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, maximum_error, maximum_kernel_width, output_array_name, use_image_spacing, variance) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorFloat64Parameter maximum_error: The algorithm will size the discrete kernel so that the error resulting from truncation of the kernel is no greater than MaximumError. The default is 0.01 in each dimension. :param nx.UInt32Parameter maximum_kernel_width: Set the kernel to be no wider than MaximumKernelWidth pixels, even if MaximumError demands it. The default is 32 pixels. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.BoolParameter use_image_spacing: Set/Get whether or not the filter will use the spacing of the input image in its calculations. Use On to take the image spacing information into account and to specify the Gaussian variance in real world units; use Off to ignore the image spacing and to specify the Gaussian variance in voxel units. Default is On. :param nx.VectorFloat64Parameter variance: The variance for the discrete Gaussian kernel. Sets the variance independently for each dimension, but see also SetVariance(const double v) . The default is 0.0 in each dimension. If UseImageSpacing is true, the units are the physical units of your image. If UseImageSpacing is false then the units are pixels. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Double Threshold Image Filter --------------------------------- .. index:: pair: Filter Human Names; ITK Double Threshold Image Filter .. index:: pair: Filter Class Names; ITKDoubleThresholdImageFilter .. _ITKDoubleThresholdImageFilter: .. py:class:: ITKDoubleThresholdImageFilter Double threshold addresses the difficulty in selecting a threshold that will select the objects of interest without selecting extraneous objects. Double threshold considers two threshold ranges: a narrow range and a wide range (where the wide range encompasses the narrow range). If the wide range was used for a traditional threshold (where values inside the range map to the foreground and values outside the range map to the background), many extraneous pixels may survive the threshold operation. If the narrow range was used for a traditional threshold, then too few pixels may survive the threshold. `Link to the full online documentation for ITKDoubleThresholdImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Fully Connected | fully_connected | +-------------------------+---------------------------+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Inside Value | inside_value | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ | Outside Value | outside_value | +-------------------------+---------------------------+ | Threshold1 | threshold1 | +-------------------------+---------------------------+ | Threshold2 | threshold2 | +-------------------------+---------------------------+ | Threshold3 | threshold3 | +-------------------------+---------------------------+ | Threshold4 | threshold4 | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, inside_value, output_array_name, outside_value, threshold1, threshold2, threshold3, threshold4) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.UInt8Parameter inside_value: Set the 'inside' pixel value. The default value NumericTraits::max() :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.UInt8Parameter outside_value: Set the 'outside' pixel value. The default value NumericTraits::ZeroValue() . :param nx.Float64Parameter threshold1: Set the thresholds. Four thresholds should be specified. The two lower thresholds default to NumericTraits::NonpositiveMin() . The two upper thresholds default NumericTraits::max . Threshold1 <= Threshold2 <= Threshold3 <= Threshold4. :param nx.Float64Parameter threshold2: Set the thresholds. Four thresholds should be specified. The two lower thresholds default to NumericTraits::NonpositiveMin() . The two upper thresholds default NumericTraits::max . Threshold1 <= Threshold2 <= Threshold3 <= Threshold4. :param nx.Float64Parameter threshold3: Set the thresholds. Four thresholds should be specified. The two lower thresholds default to NumericTraits::NonpositiveMin() . The two upper thresholds default NumericTraits::max . Threshold1 <= Threshold2 <= Threshold3 <= Threshold4. :param nx.Float64Parameter threshold4: Set the thresholds. Four thresholds should be specified. The two lower thresholds default to NumericTraits::NonpositiveMin() . The two upper thresholds default NumericTraits::max . Threshold1 <= Threshold2 <= Threshold3 <= Threshold4. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Erode Object Morphology Image Filter ---------------------------------------- .. index:: pair: Filter Human Names; ITK Erode Object Morphology Image Filter .. index:: pair: Filter Class Names; ITKErodeObjectMorphologyImageFilter .. _ITKErodeObjectMorphologyImageFilter: .. py:class:: ITKErodeObjectMorphologyImageFilter Erosion of an image using binary morphology. Pixel values matching the object value are considered the "object" and all other pixels are "background". This is useful in processing mask images containing only one object. `Link to the full online documentation for ITKErodeObjectMorphologyImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Background Value | background_value | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Kernel Radius | kernel_radius | +------------------+---------------------------+ | Kernel Type | kernel_type_index | +------------------+---------------------------+ | Object Value | object_value | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, background_value, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, object_value, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter background_value: Set the value to be assigned to eroded pixels :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.Float64Parameter object_value: The pixel value of the 'Object' to be dilated :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Exp Image Filter -------------------- .. index:: pair: Filter Human Names; ITK Exp Image Filter .. index:: pair: Filter Class Names; ITKExpImageFilter .. _ITKExpImageFilter: .. py:class:: ITKExpImageFilter The computation is performed using std::exp(x). `Link to the full online documentation for ITKExpImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Exp Negative Image Filter ----------------------------- .. index:: pair: Filter Human Names; ITK Exp Negative Image Filter .. index:: pair: Filter Class Names; ITKExpNegativeImageFilter .. _ITKExpNegativeImageFilter: .. py:class:: ITKExpNegativeImageFilter Every output pixel is equal to std::exp(-K.x ). where x is the intensity of the homologous input pixel, and K is a user-provided constant. `Link to the full online documentation for ITKExpNegativeImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Gradient Anisotropic Diffusion Image Filter ----------------------------------------------- .. index:: pair: Filter Human Names; ITK Gradient Anisotropic Diffusion Image Filter .. index:: pair: Filter Class Names; ITKGradientAnisotropicDiffusionImageFilter .. _ITKGradientAnisotropicDiffusionImageFilter: .. py:class:: ITKGradientAnisotropicDiffusionImageFilter For detailed information on anisotropic diffusion, see itkAnisotropicDiffusionFunction and itkGradientNDAnisotropicDiffusionFunction. `Link to the full online documentation for ITKGradientAnisotropicDiffusionImageFilter `_ Mapping of UI display to python named argument +-------------------------------------+-------------------------------------+ | UI Display | Python Named Argument | +=====================================+=====================================+ | Conductance Parameter | conductance_parameter | +-------------------------------------+-------------------------------------+ | Conductance Scaling Update Interval | conductance_scaling_update_interval | +-------------------------------------+-------------------------------------+ | Input Cell Data | input_image_data_path | +-------------------------------------+-------------------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------------------+-------------------------------------+ | Number Of Iterations | number_of_iterations | +-------------------------------------+-------------------------------------+ | Output Image Data Array | output_array_name | +-------------------------------------+-------------------------------------+ | Time Step | time_step | +-------------------------------------+-------------------------------------+ .. py:method:: Execute(data_structure, conductance_parameter, conductance_scaling_update_interval, input_image_data_path, input_image_geometry_path, number_of_iterations, output_array_name, time_step) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter conductance_parameter: The conductance parameter controls the sensitivity of the conductance term in the basic anisotropic diffusion equation :param nx.UInt32Parameter conductance_scaling_update_interval: The interval between conductance updates. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.UInt32Parameter number_of_iterations: Specifies the number of iterations (time-step updates) that the solver will perform to produce a solution image :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.Float64Parameter time_step: The time step to be used for each iteration. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Gradient Magnitude Image Filter ----------------------------------- .. index:: pair: Filter Human Names; ITK Gradient Magnitude Image Filter .. index:: pair: Filter Class Names; ITKGradientMagnitudeImageFilter .. _ITKGradientMagnitudeImageFilter: .. py:class:: ITKGradientMagnitudeImageFilter Computes the gradient magnitude of an image region at each pixel. `Link to the full online documentation for ITKGradientMagnitudeImageFilter `_ Mapping of UI display to python named argument +-------------------+---------------------------+ | UI Display | Python Named Argument | +===================+===========================+ | Input Cell Data | input_image_data_path | +-------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------+---------------------------+ | Output Cell Data | output_array_name | +-------------------+---------------------------+ | Use Image Spacing | use_image_spacing | +-------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name, use_image_spacing) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.BoolParameter use_image_spacing: Set/Get whether or not the filter will use the spacing of the input image in the computation of the derivatives. Use On to compute the gradient in physical space; use Off to ignore image spacing and to compute the gradient in isotropic voxel space. Default is On. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Gradient Magnitude Recursive Gaussian Image Filter ------------------------------------------------------ .. index:: pair: Filter Human Names; ITK Gradient Magnitude Recursive Gaussian Image Filter .. index:: pair: Filter Class Names; ITKGradientMagnitudeRecursiveGaussianImageFilter .. _ITKGradientMagnitudeRecursiveGaussianImageFilter: .. py:class:: ITKGradientMagnitudeRecursiveGaussianImageFilter This filter is implemented using the recursive gaussian filters `Link to the full online documentation for ITKGradientMagnitudeRecursiveGaussianImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Normalize Across Scale | normalize_across_scale | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ | Sigma | sigma | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, normalize_across_scale, output_array_name, sigma) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.BoolParameter normalize_across_scale: Set/Get the normalization factor that will be used for the Gaussian. RecursiveGaussianImageFilter::SetNormalizeAcrossScale :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.Float64Parameter sigma: Set/Get Sigma value. Sigma is measured in the units of image spacing. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Grayscale Dilate Image Filter --------------------------------- .. index:: pair: Filter Human Names; ITK Grayscale Dilate Image Filter .. index:: pair: Filter Class Names; ITKGrayscaleDilateImageFilter .. _ITKGrayscaleDilateImageFilter: .. py:class:: ITKGrayscaleDilateImageFilter Dilate an image using grayscale morphology. Dilation takes the maximum of all the pixels identified by the structuring element. `Link to the full online documentation for ITKGrayscaleDilateImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Kernel Radius | kernel_radius | +------------------+---------------------------+ | Kernel Type | kernel_type_index | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Grayscale Erode Image Filter -------------------------------- .. index:: pair: Filter Human Names; ITK Grayscale Erode Image Filter .. index:: pair: Filter Class Names; ITKGrayscaleErodeImageFilter .. _ITKGrayscaleErodeImageFilter: .. py:class:: ITKGrayscaleErodeImageFilter Erode an image using grayscale morphology. Erosion takes the maximum of all the pixels identified by the structuring element. `Link to the full online documentation for ITKGrayscaleErodeImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Kernel Radius | kernel_radius | +------------------+---------------------------+ | Kernel Type | kernel_type_index | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Grayscale Fillhole Image Filter ----------------------------------- .. index:: pair: Filter Human Names; ITK Grayscale Fillhole Image Filter .. index:: pair: Filter Class Names; ITKGrayscaleFillholeImageFilter .. _ITKGrayscaleFillholeImageFilter: .. py:class:: ITKGrayscaleFillholeImageFilter GrayscaleFillholeImageFilter fills holes in a grayscale image. Holes are local minima in the grayscale topography that are not connected to boundaries of the image. Gray level values adjacent to a hole are extrapolated across the hole. `Link to the full online documentation for ITKGrayscaleFillholeImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Fully Connected | fully_connected | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Grayscale Grind Peak Image Filter ------------------------------------- .. index:: pair: Filter Human Names; ITK Grayscale Grind Peak Image Filter .. index:: pair: Filter Class Names; ITKGrayscaleGrindPeakImageFilter .. _ITKGrayscaleGrindPeakImageFilter: .. py:class:: ITKGrayscaleGrindPeakImageFilter GrayscaleGrindPeakImageFilter removes peaks in a grayscale image. Peaks are local maxima in the grayscale topography that are not connected to boundaries of the image. Gray level values adjacent to a peak are extrapolated through the peak. `Link to the full online documentation for ITKGrayscaleGrindPeakImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Fully Connected | fully_connected | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Grayscale Morphological Closing Image Filter ------------------------------------------------ .. index:: pair: Filter Human Names; ITK Grayscale Morphological Closing Image Filter .. index:: pair: Filter Class Names; ITKGrayscaleMorphologicalClosingImageFilter .. _ITKGrayscaleMorphologicalClosingImageFilter: .. py:class:: ITKGrayscaleMorphologicalClosingImageFilter Close an image using grayscale morphology. `Link to the full online documentation for ITKGrayscaleMorphologicalClosingImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Kernel Radius | kernel_radius | +------------------+---------------------------+ | Kernel Type | kernel_type_index | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Safe Border | safe_border | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, safe_border) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.BoolParameter safe_border: A safe border is added to input image to avoid borders effects and remove it once the closing is done :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Grayscale Morphological Opening Image Filter ------------------------------------------------ .. index:: pair: Filter Human Names; ITK Grayscale Morphological Opening Image Filter .. index:: pair: Filter Class Names; ITKGrayscaleMorphologicalOpeningImageFilter .. _ITKGrayscaleMorphologicalOpeningImageFilter: .. py:class:: ITKGrayscaleMorphologicalOpeningImageFilter Open an image using grayscale morphology. `Link to the full online documentation for ITKGrayscaleMorphologicalOpeningImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Kernel Radius | kernel_radius | +------------------+---------------------------+ | Kernel Type | kernel_type_index | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Safe Border | safe_border | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, safe_border) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.BoolParameter safe_border: A safe border is added to input image to avoid borders effects and remove it once the closing is done :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK H Convex Image Filter ------------------------- .. index:: pair: Filter Human Names; ITK H Convex Image Filter .. index:: pair: Filter Class Names; ITKHConvexImageFilter .. _ITKHConvexImageFilter: .. py:class:: ITKHConvexImageFilter HConvexImageFilter extract local maxima that are more than h intensity units above the (local) background. This has the effect of extracting objects that are brighter than background by at least h intensity units. `Link to the full online documentation for ITKHConvexImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Fully Connected | fully_connected | +------------------+---------------------------+ | Height | height | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, fully_connected, height, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.Float64Parameter height: Set/Get the height that a local maximum must be above the local background (local contrast) in order to survive the processing. Local maxima below this value are replaced with an estimate of the local background. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK H Maxima Image Filter ------------------------- .. index:: pair: Filter Human Names; ITK H Maxima Image Filter .. index:: pair: Filter Class Names; ITKHMaximaImageFilter .. _ITKHMaximaImageFilter: .. py:class:: ITKHMaximaImageFilter HMaximaImageFilter suppresses local maxima that are less than h intensity units above the (local) background. This has the effect of smoothing over the "high" parts of the noise in the image without smoothing over large changes in intensity (region boundaries). See the HMinimaImageFilter to suppress the local minima whose depth is less than h intensity units below the (local) background. `Link to the full online documentation for ITKHMaximaImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Height | height | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, height, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter height: Set/Get the height that a local maximum must be above the local background (local contrast) in order to survive the processing. Local maxima below this value are replaced with an estimate of the local background. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK H Minima Image Filter ------------------------- .. index:: pair: Filter Human Names; ITK H Minima Image Filter .. index:: pair: Filter Class Names; ITKHMinimaImageFilter .. _ITKHMinimaImageFilter: .. py:class:: ITKHMinimaImageFilter HMinimaImageFilter suppresses local minima that are less than h intensity units below the (local) background. This has the effect of smoothing over the "low" parts of the noise in the image without smoothing over large changes in intensity (region boundaries). See the HMaximaImageFilter to suppress the local maxima whose height is less than h intensity units above the (local) background. `Link to the full online documentation for ITKHMinimaImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Fully Connected | fully_connected | +------------------+---------------------------+ | Height | height | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, fully_connected, height, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.Float64Parameter height: Set/Get the height that a local maximum must be above the local background (local contrast) in order to survive the processing. Local maxima below this value are replaced with an estimate of the local background. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` Read Image (ITK) ---------------- .. index:: pair: Filter Human Names; Read Image (ITK) .. index:: pair: Filter Class Names; ITKImageReaderFilter .. _ITKImageReaderFilter: .. py:class:: ITKImageReaderFilter Reads images through the ITK software library `https://www.itk.org `_ `Link to the full online documentation for ITKImageReaderFilter `_ Mapping of UI display to python named argument +--------------------------------------------+----------------------------+ | UI Display | Python Named Argument | +============================================+============================+ | Created Cell Attribute Matrix | cell_attribute_matrix_name | +--------------------------------------------+----------------------------+ | Put Input Origin at the Center of Geometry | center_origin | +--------------------------------------------+----------------------------+ | Set Image Data Type | change_image_data_type | +--------------------------------------------+----------------------------+ | Set Origin | change_origin | +--------------------------------------------+----------------------------+ | Set Spacing | change_spacing | +--------------------------------------------+----------------------------+ | File | file_name | +--------------------------------------------+----------------------------+ | Created Cell Data | image_data_array_name | +--------------------------------------------+----------------------------+ | Output Data Type | image_data_type_index | +--------------------------------------------+----------------------------+ | Length Unit | length_unit_index | +--------------------------------------------+----------------------------+ | Origin (Physical Units) | origin | +--------------------------------------------+----------------------------+ | Created Image Geometry | output_geometry_path | +--------------------------------------------+----------------------------+ | Spacing (Physical Units) | spacing | +--------------------------------------------+----------------------------+ .. py:method:: Execute(data_structure, cell_attribute_matrix_name, center_origin, change_image_data_type, change_origin, change_spacing, file_name, image_data_array_name, image_data_type_index, length_unit_index, origin, output_geometry_path, spacing) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.DataObjectNameParameter cell_attribute_matrix_name: The name of the created cell attribute matrix :param nx.BoolParameter center_origin: Specifies if the origin should be aligned with the corner (false) or center (true) :param nx.BoolParameter change_image_data_type: Set the final created image data type. :param nx.BoolParameter change_origin: Specifies if the origin should be changed :param nx.BoolParameter change_spacing: Specifies if the spacing should be changed :param nx.FileSystemPathParameter file_name: Input image file :param nx.DataObjectNameParameter image_data_array_name: The name of the created image data array. Will be stored in the created Cell Attribute Matrix :param nx.ChoicesParameter image_data_type_index: Numeric Type of data to create :param nx.ChoicesParameter length_unit_index: The length unit that will be set into the created image geometry :param nx.VectorFloat64Parameter origin: Specifies the new origin values in physical units. :param nx.DataGroupCreationParameter output_geometry_path: The path to the created Image Geometry :param nx.VectorFloat64Parameter spacing: Specifies the new spacing values in physical units. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` Write Image (ITK) ----------------- .. index:: pair: Filter Human Names; Write Image (ITK) .. index:: pair: Filter Class Names; ITKImageWriterFilter .. _ITKImageWriterFilter: .. py:class:: ITKImageWriterFilter This **Filter** will save images based on an array that represents grayscale, RGB or ARGB color values. If the input array represents a 3D volume, the **Filter** will output a series of slices along one of the orthogonal axes. The options are to produce XY slices along the Z axis, XZ slices along the Y axis or YZ slices along the X axis. The user has the option to save in one of 3 standard image formats: TIF, BMP, or PNG. The output files will be numbered sequentially starting at zero (0) and ending at the total dimensions for the chosen axis. For example, if the Z axis has 117 dimensions, 117 XY image files will be produced and numbered 0 to 116. Unless the data is a single slice then only a single image will be produced using the name given in the Output File parameter. `Link to the full online documentation for ITKImageWriterFilter `_ Mapping of UI display to python named argument +------------------------+---------------------------+ | UI Display | Python Named Argument | +========================+===========================+ | Output File | file_name | +------------------------+---------------------------+ | Input Image Data Array | image_array_path | +------------------------+---------------------------+ | Index Offset | index_offset | +------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------------+---------------------------+ | Plane | plane_index | +------------------------+---------------------------+ .. py:method:: Execute(data_structure, file_name, image_array_path, index_offset, input_image_geometry_path, plane_index) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.FileSystemPathParameter file_name: Path to the output file to write. :param nx.ArraySelectionParameter image_array_path: The image data that will be processed by this filter. :param nx.UInt64Parameter index_offset: This is the starting index when writing mulitple images :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.ChoicesParameter plane_index: Selection for plane normal for writing the images (XY, XZ, or YZ) :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` Read Fiji Montage (ITK) ----------------------- .. index:: pair: Filter Human Names; Read Fiji Montage (ITK) .. index:: pair: Filter Class Names; ITKImportFijiMontageFilter .. _ITKImportFijiMontageFilter: .. py:class:: ITKImportFijiMontageFilter Imports multiple images for the purpose of montage assembly. Each image is stored in it's own *DataContaner/AttributeMatrix/AttributeArray* where the name of the *DataContainer* is based off the row & column index of the montage. The filter assumes that the Configuration File is in the same folder as the images. The created *AttributeMatrix* and *AttributeArray* will have the same name. The image files **MUST** be located in the same directory as the Fiji Configuration File. `Link to the full online documentation for ITKImportFijiMontageFilter `_ Mapping of UI display to python named argument +------------------------------------------+----------------------------+ | UI Display | Python Named Argument | +==========================================+============================+ | Cell Attribute Matrix Name | cell_attribute_matrix_name | +------------------------------------------+----------------------------+ | Set Image Data Type | change_image_data_type | +------------------------------------------+----------------------------+ | Change Origin | change_origin | +------------------------------------------+----------------------------+ | Color Weighting | color_weights | +------------------------------------------+----------------------------+ | Convert To GrayScale | convert_to_gray_scale | +------------------------------------------+----------------------------+ | Image Geometry Prefix | data_container_path | +------------------------------------------+----------------------------+ | Name of Created DataGroup | data_group_name | +------------------------------------------+----------------------------+ | Image DataArray Name | image_data_array_name | +------------------------------------------+----------------------------+ | Output Data Type | image_data_type_index | +------------------------------------------+----------------------------+ | Fiji Configuration File | input_file | +------------------------------------------+----------------------------+ | Length Unit | length_unit_index | +------------------------------------------+----------------------------+ | Origin | origin | +------------------------------------------+----------------------------+ | Parent Imported Images Under a DataGroup | parent_data_group | +------------------------------------------+----------------------------+ .. py:method:: Execute(data_structure, cell_attribute_matrix_name, change_image_data_type, change_origin, color_weights, convert_to_gray_scale, data_container_path, data_group_name, image_data_array_name, image_data_type_index, input_file, length_unit_index, origin, parent_data_group) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.StringParameter cell_attribute_matrix_name: The name of the Cell Attribute Matrix :param nx.BoolParameter change_image_data_type: Set the final created image data type. :param nx.BoolParameter change_origin: Set the origin of the mosaic to a user defined value :param nx.VectorFloat32Parameter color_weights: The luminosity values for the conversion :param nx.BoolParameter convert_to_gray_scale: The filter will show an error if the images are already in grayscale format :param nx.StringParameter data_container_path: A prefix that can be used for each Image Geometry :param nx.StringParameter data_group_name: Name of the overarching parent DataGroup :param nx.StringParameter image_data_array_name: The name of the import image data :param nx.ChoicesParameter image_data_type_index: Numeric Type of data to create :param nx.FileSystemPathParameter input_file: This is the configuration file in the same directory as all of the identified geometries :param nx.ChoicesParameter length_unit_index: The length unit that will be set into the created image geometry :param nx.VectorFloat32Parameter origin: The new origin of the mosaic :param nx.BoolParameter parent_data_group: Create a new DataGroup to hold the imported images :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` Read Images [3D Stack] (ITK) ---------------------------- .. index:: pair: Filter Human Names; Read Images [3D Stack] (ITK) .. index:: pair: Filter Class Names; ITKImportImageStackFilter .. _ITKImportImageStackFilter: .. py:class:: ITKImportImageStackFilter Read in a stack of 2D images and stack the images into a 3D Volume using the ITK library. Supports most common scalar pixel types and the many file formats supported by ITK.The filter will create a new Image Geometry. The user can specify a value for the origin and the spacing if the defaults are not appropriate. The default value for the origin will be at (0, 0, 0) and the default spacing value will be (1.0, 1.0, 1.0). If the user needs to have the create Image Geometry located in a different location in the global reference frame, the user can change the default origin value. The "origin" of the image is at a normal Cartesian style origin.The user can decide to scale the images as they are being read in by turning on the Scale Images option, and setting a scale value. A scale value of 10.0 resamples the images in the stack to one-tenth the number of pixels, a scale value of 200.0 resamples the images in the stack to double the number of pixels. The default scale value is 100.0. `Link to the full online documentation for ITKImportImageStackFilter `_ Mapping of UI display to python named argument +---------------------------+----------------------------+ | UI Display | Python Named Argument | +===========================+============================+ | Cell Data Name | cell_attribute_matrix_name | +---------------------------+----------------------------+ | Set Image Data Type | change_image_data_type | +---------------------------+----------------------------+ | Color Weighting | color_weights | +---------------------------+----------------------------+ | Convert To GrayScale | convert_to_gray_scale | +---------------------------+----------------------------+ | Exact 2D Dimensions | exact_xy_dimensions | +---------------------------+----------------------------+ | Created Image Data | image_data_array_name | +---------------------------+----------------------------+ | Output Data Type | image_data_type_index | +---------------------------+----------------------------+ | Optional Slice Operations | image_transform_index | +---------------------------+----------------------------+ | Input File List | input_file_list_object | +---------------------------+----------------------------+ | Origin | origin | +---------------------------+----------------------------+ | Created Image Geometry | output_image_geometry_path | +---------------------------+----------------------------+ | Resample Images | resample_images_index | +---------------------------+----------------------------+ | Scaling | scaling | +---------------------------+----------------------------+ | Spacing | spacing | +---------------------------+----------------------------+ .. py:method:: Execute(data_structure, cell_attribute_matrix_name, change_image_data_type, color_weights, convert_to_gray_scale, exact_xy_dimensions, image_data_array_name, image_data_type_index, image_transform_index, input_file_list_object, origin, output_image_geometry_path, resample_images_index, scaling, spacing) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.DataObjectNameParameter cell_attribute_matrix_name: The name of the created cell attribute matrix :param nx.BoolParameter change_image_data_type: Set the final created image data type. :param nx.VectorFloat32Parameter color_weights: RGB weights for the grayscale conversion using the luminosity algorithm. :param nx.BoolParameter convert_to_gray_scale: The filter will show an error if the images are already in grayscale format :param nx.VectorUInt64Parameter exact_xy_dimensions: The supplied dimensions will be used to determine the resampled output geometry size. See associated Filter documentation for further detail. :param nx.DataObjectNameParameter image_data_array_name: The path to the created image data array :param nx.ChoicesParameter image_data_type_index: Numeric Type of data to create :param nx.ChoicesParameter image_transform_index: Operation that is performed on each slice. 0=None, 1=Flip about X, 2=Flip about Y :param nx.GeneratedFileListParameter input_file_list_object: The list of 2D image files to be read in to a 3D volume :param nx.VectorFloat32Parameter origin: The origin of the 3D volume :param nx.DataGroupCreationParameter output_image_geometry_path: The path to the created Image Geometry :param nx.ChoicesParameter resample_images_index: Mode can be [0] Do Not Rescale, [1] Scaling as Percent, [2] Exact X/Y Dimensions For Resampling Along Z Axis :param nx.Float32Parameter scaling: The scaling of the 3D volume, in percentages. Percentage must be greater than or equal to 1.0f. Larger percentages will cause more voxels, smaller percentages will cause less voxels. For example, 10.0 is one-tenth the original number of pixels. 200.0 is double the number of pixels. :param nx.VectorFloat32Parameter spacing: The spacing of the 3D volume :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Intensity Windowing Image Filter ------------------------------------ .. index:: pair: Filter Human Names; ITK Intensity Windowing Image Filter .. index:: pair: Filter Class Names; ITKIntensityWindowingImageFilter .. _ITKIntensityWindowingImageFilter: .. py:class:: ITKIntensityWindowingImageFilter IntensityWindowingImageFilter applies pixel-wise a linear transformation to the intensity values of input image pixels. The linear transformation is defined by the user in terms of the minimum and maximum values that the output image should have and the lower and upper limits of the intensity window of the input image. This operation is very common in visualization, and can also be applied as a convenient preprocessing operation for image segmentation. `Link to the full online documentation for ITKIntensityWindowingImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Output Maximum | output_maximum | +------------------+---------------------------+ | Output Minimum | output_minimum | +------------------+---------------------------+ | Window Maximum | window_maximum | +------------------+---------------------------+ | Window Minimum | window_minimum | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name, output_maximum, output_minimum, window_maximum, window_minimum) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.Float64Parameter output_maximum: Set/Get the values of the maximum and minimum intensities of the output image. :param nx.Float64Parameter output_minimum: Set/Get the values of the maximum and minimum intensities of the output image. :param nx.Float64Parameter window_maximum: Set/Get the values of the maximum and minimum intensities of the input intensity window. :param nx.Float64Parameter window_minimum: Set/Get the values of the maximum and minimum intensities of the input intensity window. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Invert Intensity Image Filter --------------------------------- .. index:: pair: Filter Human Names; ITK Invert Intensity Image Filter .. index:: pair: Filter Class Names; ITKInvertIntensityImageFilter .. _ITKInvertIntensityImageFilter: .. py:class:: ITKInvertIntensityImageFilter InvertIntensityImageFilter inverts intensity of pixels by subtracting pixel value to a maximum value. The maximum value can be set with SetMaximum and defaults the maximum of input pixel type. This filter can be used to invert, for example, a binary image, a distance map, etc. `Link to the full online documentation for ITKInvertIntensityImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Maximum | maximum | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, maximum, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.Float64Parameter maximum: Set/Get the maximum intensity value for the inversion. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Iso Contour Distance Image Filter ------------------------------------- .. index:: pair: Filter Human Names; ITK Iso Contour Distance Image Filter .. index:: pair: Filter Class Names; ITKIsoContourDistanceImageFilter .. _ITKIsoContourDistanceImageFilter: .. py:class:: ITKIsoContourDistanceImageFilter For standard level set algorithms, it is useful to periodically reinitialize the evolving image to prevent numerical accuracy problems in computing derivatives. This reinitialization is done by computing a signed distance map to the current level set. This class provides the first step in this reinitialization by computing an estimate of the distance from the interpolated isocontour to the pixels (or voxels) that are close to it, i.e. for which the isocontour crosses a segment between them and one of their direct neighbors. This class supports narrowbanding. If the input narrowband is provided, the algorithm will only locate the level set within the input narrowband. `Link to the full online documentation for ITKIsoContourDistanceImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Far Value | far_value | +-------------------------+---------------------------+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Level Set Value | level_set_value | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, far_value, input_image_data_path, input_image_geometry_path, level_set_value, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter far_value: Set/Get the value of the level set to be located. The default value is 0. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.Float64Parameter level_set_value: Set/Get the value of the level set to be located. The default value is 0. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Label Contour Image Filter ------------------------------ .. index:: pair: Filter Human Names; ITK Label Contour Image Filter .. index:: pair: Filter Class Names; ITKLabelContourImageFilter .. _ITKLabelContourImageFilter: .. py:class:: ITKLabelContourImageFilter LabelContourImageFilter takes a labeled image as input, where the pixels in the objects are the pixels with a value different of the BackgroundValue. Only the pixels on the contours of the objects are kept. The pixels not on the border are changed to BackgroundValue. The labels of the object are the same in the input and in the output image. `Link to the full online documentation for ITKLabelContourImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Background Value | background_value | +------------------+---------------------------+ | Fully Connected | fully_connected | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, background_value, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter background_value: Set/Get the background value used to identify the objects and mark the pixels not on the border of the objects. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. **NOTE** For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Laplacian Recursive Gaussian Image Filter --------------------------------------------- .. index:: pair: Filter Human Names; ITK Laplacian Recursive Gaussian Image Filter .. index:: pair: Filter Class Names; ITKLaplacianRecursiveGaussianImageFilter .. _ITKLaplacianRecursiveGaussianImageFilter: .. py:class:: ITKLaplacianRecursiveGaussianImageFilter Computes the Laplacian of Gaussian (LoG) of an image by convolution with the second derivative of a Gaussian. This filter is implemented using the recursive gaussian filters. `Link to the full online documentation for ITKLaplacianRecursiveGaussianImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Normalize Across Scale | normalize_across_scale | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ | Sigma | sigma | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, normalize_across_scale, output_array_name, sigma) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.BoolParameter normalize_across_scale: Define which normalization factor will be used for the Gaussian. See RecursiveGaussianImageFilter::SetNormalizeAcrossScale :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.Float64Parameter sigma: Set/Get Sigma value. Sigma is measured in the units of image spacing. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Log10 Image Filter ---------------------- .. index:: pair: Filter Human Names; ITK Log10 Image Filter .. index:: pair: Filter Class Names; ITKLog10ImageFilter .. _ITKLog10ImageFilter: .. py:class:: ITKLog10ImageFilter The computation is performed using std::log10(x). `Link to the full online documentation for ITKLog10ImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Log Image Filter -------------------- .. index:: pair: Filter Human Names; ITK Log Image Filter .. index:: pair: Filter Class Names; ITKLogImageFilter .. _ITKLogImageFilter: .. py:class:: ITKLogImageFilter !` `_ `Link to the full online documentation for ITKLogImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Mask Image Filter --------------------- .. index:: pair: Filter Human Names; ITK Mask Image Filter .. index:: pair: Filter Class Names; ITKMaskImageFilter .. _ITKMaskImageFilter: .. py:class:: ITKMaskImageFilter Mask an image with a mask. `Link to the full online documentation for ITKMaskImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | MaskImage | mask_image_data_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Outside Value | outside_value | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, mask_image_data_path, output_array_name, outside_value) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.ArraySelectionParameter mask_image_data_path: The path to the image data to be used as the mask (should be the same size as the input image) :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.Float64Parameter outside_value: Method to explicitly set the outside value of the mask. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Maximum Projection Image Filter ----------------------------------- .. index:: pair: Filter Human Names; ITK Maximum Projection Image Filter .. index:: pair: Filter Class Names; ITKMaximumProjectionImageFilter .. _ITKMaximumProjectionImageFilter: .. py:class:: ITKMaximumProjectionImageFilter This class was contributed to the Insight Journal by Gaetan Lehmann. The original paper can be found at https://www.insight-journal.org/browse/publication/71 `Link to the full online documentation for ITKMaximumProjectionImageFilter `_ Mapping of UI display to python named argument +-------------------------+----------------------------+ | UI Display | Python Named Argument | +=========================+============================+ | Input Cell Data | input_image_data_path | +-------------------------+----------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+----------------------------+ | Output Image Data Array | output_array_name | +-------------------------+----------------------------+ | Created Image Geometry | output_image_geometry_name | +-------------------------+----------------------------+ | Projection Dimension | projection_dimension | +-------------------------+----------------------------+ | Perform In-Place | remove_original_geometry | +-------------------------+----------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name, output_image_geometry_name, projection_dimension, remove_original_geometry) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.StringParameter output_image_geometry_name: The name of the projected geometry :param nx.UInt32Parameter projection_dimension: The dimension index to project. 0=Slowest moving dimension. :param nx.BoolParameter remove_original_geometry: Performs the projection in-place for the given Image Geometry :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Mean Projection Image Filter -------------------------------- .. index:: pair: Filter Human Names; ITK Mean Projection Image Filter .. index:: pair: Filter Class Names; ITKMeanProjectionImageFilter .. _ITKMeanProjectionImageFilter: .. py:class:: ITKMeanProjectionImageFilter This class was contributed to the Insight Journal by Gaetan Lehmann. The original paper can be found at https://www.insight-journal.org/browse/publication/71 `Link to the full online documentation for ITKMeanProjectionImageFilter `_ Mapping of UI display to python named argument +-------------------------+----------------------------+ | UI Display | Python Named Argument | +=========================+============================+ | Input Cell Data | input_image_data_path | +-------------------------+----------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+----------------------------+ | Output Image Data Array | output_array_name | +-------------------------+----------------------------+ | Created Image Geometry | output_image_geometry_name | +-------------------------+----------------------------+ | Projection Dimension | projection_dimension | +-------------------------+----------------------------+ | Perform In-Place | remove_original_geometry | +-------------------------+----------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name, output_image_geometry_name, projection_dimension, remove_original_geometry) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.StringParameter output_image_geometry_name: The name of the projected geometry :param nx.UInt32Parameter projection_dimension: The dimension index to project. 0=Slowest moving dimension. :param nx.BoolParameter remove_original_geometry: Performs the projection in-place for the given Image Geometry :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Median Image Filter ----------------------- .. index:: pair: Filter Human Names; ITK Median Image Filter .. index:: pair: Filter Class Names; ITKMedianImageFilter .. _ITKMedianImageFilter: .. py:class:: ITKMedianImageFilter Computes an image where a given pixel is the median value of the the pixels in a neighborhood about the corresponding input pixel. `Link to the full online documentation for ITKMedianImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Radius | radius | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name, radius) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.VectorUInt32Parameter radius: Radius Dimensions XYZ :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Median Projection Image Filter ---------------------------------- .. index:: pair: Filter Human Names; ITK Median Projection Image Filter .. index:: pair: Filter Class Names; ITKMedianProjectionImageFilter .. _ITKMedianProjectionImageFilter: .. py:class:: ITKMedianProjectionImageFilter This class was contributed to the Insight Journal by Gaetan Lehmann. The original paper can be found at https://www.insight-journal.org/browse/publication/71 `Link to the full online documentation for ITKMedianProjectionImageFilter `_ Mapping of UI display to python named argument +-------------------------+----------------------------+ | UI Display | Python Named Argument | +=========================+============================+ | Input Cell Data | input_image_data_path | +-------------------------+----------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+----------------------------+ | Output Image Data Array | output_array_name | +-------------------------+----------------------------+ | Created Image Geometry | output_image_geometry_name | +-------------------------+----------------------------+ | Projection Dimension | projection_dimension | +-------------------------+----------------------------+ | Perform In-Place | remove_original_geometry | +-------------------------+----------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name, output_image_geometry_name, projection_dimension, remove_original_geometry) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.StringParameter output_image_geometry_name: The name of the projected geometry :param nx.UInt32Parameter projection_dimension: The dimension index to project. 0=Slowest moving dimension. :param nx.BoolParameter remove_original_geometry: Performs the projection in-place for the given Image Geometry :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK MHA File Reader ------------------- .. index:: pair: Filter Human Names; ITK MHA File Reader .. index:: pair: Filter Class Names; ITKMhaFileReaderFilter .. _ITKMhaFileReaderFilter: .. py:class:: ITKMhaFileReaderFilter Reads MHA images and the transformation matrix using ITK. Some select headers from the MHA file are read. If those headers are not available then the default values are used. `Link to the full online documentation for ITKMhaFileReaderFilter `_ Mapping of UI display to python named argument +----------------------------------------+-----------------------------------+ | UI Display | Python Named Argument | +========================================+===================================+ | Apply Image Transformation To Geometry | apply_image_transformation | +----------------------------------------+-----------------------------------+ | Created Cell Attribute Matrix | cell_attribute_matrix_name | +----------------------------------------+-----------------------------------+ | Input MHA File | file_name | +----------------------------------------+-----------------------------------+ | Created Cell Data | image_data_array_name | +----------------------------------------+-----------------------------------+ | Interpolation Type | interpolation_type_index | +----------------------------------------+-----------------------------------+ | Created Image Geometry | output_geometry_path | +----------------------------------------+-----------------------------------+ | Transformation Matrix | output_transformation_matrix_path | +----------------------------------------+-----------------------------------+ | Save Image Transformation As Array | save_image_transformation | +----------------------------------------+-----------------------------------+ | Transpose Stored Transformation Matrix | transpose_transform_matrix | +----------------------------------------+-----------------------------------+ .. py:method:: Execute(data_structure, apply_image_transformation, cell_attribute_matrix_name, file_name, image_data_array_name, interpolation_type_index, output_geometry_path, output_transformation_matrix_path, save_image_transformation, transpose_transform_matrix) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.BoolParameter apply_image_transformation: When true, the transformation matrix found in the image's header metadata will be applied to the created image geometry. :param nx.DataObjectNameParameter cell_attribute_matrix_name: The name of the created cell attribute matrix :param nx.FileSystemPathParameter file_name: The input .mha file that will be read. :param nx.DataObjectNameParameter image_data_array_name: The name of the created image data array. Will be stored in the created Cell Attribute Matrix :param nx.ChoicesParameter interpolation_type_index: The type of interpolation algorithm that is used. 0=NearestNeighbor, 1=Linear :param nx.DataGroupCreationParameter output_geometry_path: The path to the created Image Geometry :param nx.ArrayCreationParameter output_transformation_matrix_path: The path to the transformation matrix data array :param nx.BoolParameter save_image_transformation: When true, the transformation matrix found in the image's header metadata will be saved as a data array in the created image geometry. :param nx.BoolParameter transpose_transform_matrix: When true, the transformation matrix found in the image's header metadata will be transposed before use. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Min Max Curvature Flow Image Filter --------------------------------------- .. index:: pair: Filter Human Names; ITK Min Max Curvature Flow Image Filter .. index:: pair: Filter Class Names; ITKMinMaxCurvatureFlowImageFilter .. _ITKMinMaxCurvatureFlowImageFilter: .. py:class:: ITKMinMaxCurvatureFlowImageFilter MinMaxCurvatureFlowImageFilter implements a curvature driven image denoising algorithm. Iso-brightness contours in the grayscale input image are viewed as a level set. The level set is then evolved using a curvature-based speed function: `Link to the full online documentation for ITKMinMaxCurvatureFlowImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Number Of Iterations | number_of_iterations | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ | Stencil Radius | stencil_radius | +-------------------------+---------------------------+ | Time Step | time_step | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, number_of_iterations, output_array_name, stencil_radius, time_step) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.UInt32Parameter number_of_iterations: Specifies the number of iterations (time-step updates) that the solver will perform to produce a solution image :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.Int32Parameter stencil_radius: Set/Get the stencil radius. :param nx.Float64Parameter time_step: The time step to be used for each iteration. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Minimum Projection Image Filter ----------------------------------- .. index:: pair: Filter Human Names; ITK Minimum Projection Image Filter .. index:: pair: Filter Class Names; ITKMinimumProjectionImageFilter .. _ITKMinimumProjectionImageFilter: .. py:class:: ITKMinimumProjectionImageFilter This class was contributed to the Insight Journal by Gaetan Lehmann. The original paper can be found at https://www.insight-journal.org/browse/publication/71 `Link to the full online documentation for ITKMinimumProjectionImageFilter `_ Mapping of UI display to python named argument +-------------------------+----------------------------+ | UI Display | Python Named Argument | +=========================+============================+ | Input Cell Data | input_image_data_path | +-------------------------+----------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+----------------------------+ | Output Image Data Array | output_array_name | +-------------------------+----------------------------+ | Created Image Geometry | output_image_geometry_name | +-------------------------+----------------------------+ | Projection Dimension | projection_dimension | +-------------------------+----------------------------+ | Perform In-Place | remove_original_geometry | +-------------------------+----------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name, output_image_geometry_name, projection_dimension, remove_original_geometry) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.StringParameter output_image_geometry_name: The name of the projected geometry :param nx.UInt32Parameter projection_dimension: The dimension index to project. 0=Slowest moving dimension. :param nx.BoolParameter remove_original_geometry: Performs the projection in-place for the given Image Geometry :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Morphological Gradient Image Filter --------------------------------------- .. index:: pair: Filter Human Names; ITK Morphological Gradient Image Filter .. index:: pair: Filter Class Names; ITKMorphologicalGradientImageFilter .. _ITKMorphologicalGradientImageFilter: .. py:class:: ITKMorphologicalGradientImageFilter The structuring element is assumed to be composed of binary values (zero or one). Only elements of the structuring element having values > 0 are candidates for affecting the center pixel.* MorphologyImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter `Link to the full online documentation for ITKMorphologicalGradientImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Kernel Radius | kernel_radius | +------------------+---------------------------+ | Kernel Type | kernel_type_index | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Morphological Watershed Image Filter ---------------------------------------- .. index:: pair: Filter Human Names; ITK Morphological Watershed Image Filter .. index:: pair: Filter Class Names; ITKMorphologicalWatershedImageFilter .. _ITKMorphologicalWatershedImageFilter: .. py:class:: ITKMorphologicalWatershedImageFilter Watershed pixel are labeled 0. TOutputImage should be an integer type. Labels of output image are in no particular order. You can reorder the labels such that object labels are consecutive and sorted based on object size by passing the output of this filter to a RelabelComponentImageFilter . `Link to the full online documentation for ITKMorphologicalWatershedImageFilter `_ Mapping of UI display to python named argument +-------------------+---------------------------+ | UI Display | Python Named Argument | +===================+===========================+ | Fully Connected | fully_connected | +-------------------+---------------------------+ | Input Cell Data | input_image_data_path | +-------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------+---------------------------+ | Level | level | +-------------------+---------------------------+ | MarkWatershedLine | mark_watershed_line | +-------------------+---------------------------+ | Output Cell Data | output_array_name | +-------------------+---------------------------+ .. py:method:: Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, level, mark_watershed_line, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.Float64Parameter level: Set the 'level' variable to the filter :param nx.BoolParameter mark_watershed_line: Set/Get whether the watershed pixel must be marked or not. Default is true. Set it to false do not only avoid writing watershed pixels, it also decrease algorithm complexity. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Normalize Image Filter -------------------------- .. index:: pair: Filter Human Names; ITK Normalize Image Filter .. index:: pair: Filter Class Names; ITKNormalizeImageFilter .. _ITKNormalizeImageFilter: .. py:class:: ITKNormalizeImageFilter NormalizeImageFilter shifts and scales an image so that the pixels in the image have a zero mean and unit variance. This filter uses StatisticsImageFilter to compute the mean and variance of the input and then applies ShiftScaleImageFilter to shift and scale the pixels. `Link to the full online documentation for ITKNormalizeImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Not Image Filter -------------------- .. index:: pair: Filter Human Names; ITK Not Image Filter .. index:: pair: Filter Class Names; ITKNotImageFilter .. _ITKNotImageFilter: .. py:class:: ITKNotImageFilter This class is templated over the type of an input image and the type of the output image. Numeric conversions (castings) are done by the C++ defaults. `Link to the full online documentation for ITKNotImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Opening By Reconstruction Image Filter ------------------------------------------ .. index:: pair: Filter Human Names; ITK Opening By Reconstruction Image Filter .. index:: pair: Filter Class Names; ITKOpeningByReconstructionImageFilter .. _ITKOpeningByReconstructionImageFilter: .. py:class:: ITKOpeningByReconstructionImageFilter This filter preserves regions, in the foreground, that can completely contain the structuring element. At the same time, this filter eliminates all other regions of foreground pixels. Contrary to the morphological opening, the opening by reconstruction preserves the shape of the components that are not removed by erosion. The opening by reconstruction of an image "f" is defined as: `Link to the full online documentation for ITKOpeningByReconstructionImageFilter `_ Mapping of UI display to python named argument +---------------------+---------------------------+ | UI Display | Python Named Argument | +=====================+===========================+ | Fully Connected | fully_connected | +---------------------+---------------------------+ | Input Cell Data | input_image_data_path | +---------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +---------------------+---------------------------+ | Kernel Radius | kernel_radius | +---------------------+---------------------------+ | Kernel Type | kernel_type_index | +---------------------+---------------------------+ | Output Cell Data | output_array_name | +---------------------+---------------------------+ | PreserveIntensities | preserve_intensities | +---------------------+---------------------------+ .. py:method:: Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, preserve_intensities) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.BoolParameter preserve_intensities: Set/Get whether the original intensities of the image retained for those pixels unaffected by the opening by reconstruction. If Off, the output pixel contrast will be reduced. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Otsu Multiple Thresholds Image Filter ----------------------------------------- .. index:: pair: Filter Human Names; ITK Otsu Multiple Thresholds Image Filter .. index:: pair: Filter Class Names; ITKOtsuMultipleThresholdsImageFilter .. _ITKOtsuMultipleThresholdsImageFilter: .. py:class:: ITKOtsuMultipleThresholdsImageFilter This filter creates a labeled image that separates the input image into various classes. The filter computes the thresholds using the OtsuMultipleThresholdsCalculator and applies those thresholds to the input image using the ThresholdLabelerImageFilter . The NumberOfHistogramBins and NumberOfThresholds can be set for the Calculator. The LabelOffset can be set for the ThresholdLabelerImageFilter . `Link to the full online documentation for ITKOtsuMultipleThresholdsImageFilter `_ Mapping of UI display to python named argument +--------------------------+---------------------------+ | UI Display | Python Named Argument | +==========================+===========================+ | Input Cell Data | input_image_data_path | +--------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +--------------------------+---------------------------+ | Label Offset | label_offset | +--------------------------+---------------------------+ | Number Of Histogram Bins | number_of_histogram_bins | +--------------------------+---------------------------+ | Number Of Thresholds | number_of_thresholds | +--------------------------+---------------------------+ | Output Cell Data | output_array_name | +--------------------------+---------------------------+ | ReturnBinMidpoint | return_bin_midpoint | +--------------------------+---------------------------+ | Valley Emphasis | valley_emphasis | +--------------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, label_offset, number_of_histogram_bins, number_of_thresholds, output_array_name, return_bin_midpoint, valley_emphasis) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.UInt8Parameter label_offset: Set/Get the offset which labels have to start from. Default is 0. :param nx.UInt32Parameter number_of_histogram_bins: Set/Get the number of histogram bins. Default is 128. :param nx.UInt8Parameter number_of_thresholds: Set/Get the number of thresholds. Default is 1. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.BoolParameter return_bin_midpoint: Should the threshold value be mid-point of the bin or the maximum? Default is to return bin maximum. :param nx.BoolParameter valley_emphasis: Set/Get the use of valley emphasis. Default is false. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Regional Maxima Image Filter -------------------------------- .. index:: pair: Filter Human Names; ITK Regional Maxima Image Filter .. index:: pair: Filter Class Names; ITKRegionalMaximaImageFilter .. _ITKRegionalMaximaImageFilter: .. py:class:: ITKRegionalMaximaImageFilter Regional maxima are flat zones surrounded by pixels of lower value. `Link to the full online documentation for ITKRegionalMaximaImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Background Value | background_value | +-------------------------+---------------------------+ | Flat Is Maxima | flat_is_maxima | +-------------------------+---------------------------+ | Foreground Value | foreground_value | +-------------------------+---------------------------+ | Fully Connected | fully_connected | +-------------------------+---------------------------+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, background_value, flat_is_maxima, foreground_value, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter background_value: Set/Get the value used as 'background' in the output image. Defaults to NumericTraits::NonpositiveMin() . :param nx.BoolParameter flat_is_maxima: Set/Get whether a flat image must be considered as a maxima or not. Defaults to true. :param nx.Float64Parameter foreground_value: Set/Get the value in the output image to consider as 'foreground'. Defaults to maximum value of PixelType. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Regional Minima Image Filter -------------------------------- .. index:: pair: Filter Human Names; ITK Regional Minima Image Filter .. index:: pair: Filter Class Names; ITKRegionalMinimaImageFilter .. _ITKRegionalMinimaImageFilter: .. py:class:: ITKRegionalMinimaImageFilter Regional minima are flat zones surrounded by pixels of greater value. `Link to the full online documentation for ITKRegionalMinimaImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Background Value | background_value | +-------------------------+---------------------------+ | Flat Is Minima | flat_is_minima | +-------------------------+---------------------------+ | Foreground Value | foreground_value | +-------------------------+---------------------------+ | Fully Connected | fully_connected | +-------------------------+---------------------------+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, background_value, flat_is_minima, foreground_value, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter background_value: Set/Get the value used as 'background' in the output image. Defaults to NumericTraits::NonpositiveMin() . :param nx.BoolParameter flat_is_minima: Set/Get whether a flat image must be considered as a minima or not. Defaults to true. :param nx.Float64Parameter foreground_value: Set/Get the value in the output image to consider as 'foreground'. Defaults to maximum value of PixelType. :param nx.BoolParameter fully_connected: Set/Get whether the connected components are defined strictly by face connectivity or by face+edge+vertex connectivity. Default is FullyConnectedOff. For objects that are 1 pixel wide, use FullyConnectedOn. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Relabel Component Image Filter ---------------------------------- .. index:: pair: Filter Human Names; ITK Relabel Component Image Filter .. index:: pair: Filter Class Names; ITKRelabelComponentImageFilter .. _ITKRelabelComponentImageFilter: .. py:class:: ITKRelabelComponentImageFilter RelabelComponentImageFilter remaps the labels associated with the objects in an image (as from the output of ConnectedComponentImageFilter ) such that the label numbers are consecutive with no gaps between the label numbers used. By default, the relabeling will also sort the labels based on the size of the object: the largest object will have label #1, the second largest will have label #2, etc. If two labels have the same size their initial order is kept. The sorting by size can be disabled using SetSortByObjectSize. `Link to the full online documentation for ITKRelabelComponentImageFilter `_ Mapping of UI display to python named argument +---------------------+---------------------------+ | UI Display | Python Named Argument | +=====================+===========================+ | Input Cell Data | input_image_data_path | +---------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +---------------------+---------------------------+ | Minimum Object Size | minimum_object_size | +---------------------+---------------------------+ | Output Cell Data | output_array_name | +---------------------+---------------------------+ | SortByObjectSize | sort_by_object_size | +---------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, minimum_object_size, output_array_name, sort_by_object_size) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.UInt64Parameter minimum_object_size: Set the minimum size in pixels for an object. All objects smaller than this size will be discarded and will not appear in the output label map. NumberOfObjects will count only the objects whose pixel counts are greater than or equal to the minimum size. Call GetOriginalNumberOfObjects to find out how many objects were present in the original label map. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.BoolParameter sort_by_object_size: Controls whether the object labels are sorted by size. If false, initial order of labels is kept. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Rescale Intensity Image Filter ---------------------------------- .. index:: pair: Filter Human Names; ITK Rescale Intensity Image Filter .. index:: pair: Filter Class Names; ITKRescaleIntensityImageFilter .. _ITKRescaleIntensityImageFilter: .. py:class:: ITKRescaleIntensityImageFilter RescaleIntensityImageFilter applies pixel-wise a linear transformation to the intensity values of input image pixels. The linear transformation is defined by the user in terms of the minimum and maximum values that the output image should have. `Link to the full online documentation for ITKRescaleIntensityImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Output Maximum | output_maximum | +------------------+---------------------------+ | Output Minimum | output_minimum | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name, output_maximum, output_minimum) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.Float64Parameter output_maximum: The maximum output value that is used. :param nx.Float64Parameter output_minimum: The minimum output value that is used. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Sigmoid Image Filter ------------------------ .. index:: pair: Filter Human Names; ITK Sigmoid Image Filter .. index:: pair: Filter Class Names; ITKSigmoidImageFilter .. _ITKSigmoidImageFilter: .. py:class:: ITKSigmoidImageFilter A linear transformation is applied first on the argument of the sigmoid function. The resulting total transform is given by `Link to the full online documentation for ITKSigmoidImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Alpha | alpha | +------------------+---------------------------+ | Beta | beta | +------------------+---------------------------+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Output Maximum | output_maximum | +------------------+---------------------------+ | Output Minimum | output_minimum | +------------------+---------------------------+ .. py:method:: Execute(data_structure, alpha, beta, input_image_data_path, input_image_geometry_path, output_array_name, output_maximum, output_minimum) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter alpha: The Alpha value from the Sigmoid equation. :param nx.Float64Parameter beta: The Beta value from teh sigmoid equation :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.Float64Parameter output_maximum: The maximum output value :param nx.Float64Parameter output_minimum: The minimum output value :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Signed Danielsson Distance Map Image Filter ----------------------------------------------- .. index:: pair: Filter Human Names; ITK Signed Danielsson Distance Map Image Filter .. index:: pair: Filter Class Names; ITKSignedDanielssonDistanceMapImageFilter .. _ITKSignedDanielssonDistanceMapImageFilter: .. py:class:: ITKSignedDanielssonDistanceMapImageFilter This class is parameterized over the type of the input image and the type of the output image. `Link to the full online documentation for ITKSignedDanielssonDistanceMapImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Inside Is Positive | inside_is_positive | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ | Squared Distance | squared_distance | +-------------------------+---------------------------+ | Use Image Spacing | use_image_spacing | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, inside_is_positive, output_array_name, squared_distance, use_image_spacing) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.BoolParameter inside_is_positive: Set if the inside represents positive values in the signed distance map. By convention ON pixels are treated as inside pixels. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.BoolParameter squared_distance: Set if the distance should be squared. :param nx.BoolParameter use_image_spacing: Set if image spacing should be used in computing distances. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Signed Maurer Distance Map Image Filter ------------------------------------------- .. index:: pair: Filter Human Names; ITK Signed Maurer Distance Map Image Filter .. index:: pair: Filter Class Names; ITKSignedMaurerDistanceMapImageFilter .. _ITKSignedMaurerDistanceMapImageFilter: .. py:class:: ITKSignedMaurerDistanceMapImageFilter Inputs and OutputsThis is an image-to-image filter. The dimensionality is arbitrary. The only dimensionality constraint is that the input and output images be of the same dimensions and size. To maintain integer arithmetic within the filter, the default output is the signed squared distance. This implies that the input image should be of type "unsigned int" or "int" whereas the output image is of type "int". Obviously, if the user wishes to utilize the image spacing or to have a filter with the Euclidean distance (as opposed to the squared distance), output image types of float or double should be used. `Link to the full online documentation for ITKSignedMaurerDistanceMapImageFilter `_ Mapping of UI display to python named argument +--------------------+---------------------------+ | UI Display | Python Named Argument | +====================+===========================+ | Background Value | background_value | +--------------------+---------------------------+ | Input Cell Data | input_image_data_path | +--------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +--------------------+---------------------------+ | Inside Is Positive | inside_is_positive | +--------------------+---------------------------+ | Output Cell Data | output_array_name | +--------------------+---------------------------+ | SquaredDistance | squared_distance | +--------------------+---------------------------+ | Use Image Spacing | use_image_spacing | +--------------------+---------------------------+ .. py:method:: Execute(data_structure, background_value, input_image_data_path, input_image_geometry_path, inside_is_positive, output_array_name, squared_distance, use_image_spacing) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.Float64Parameter background_value: Set the background value which defines the object. Usually this value is = 0. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.BoolParameter inside_is_positive: Set if the inside represents positive values in the signed distance map. By convention ON pixels are treated as inside pixels. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.BoolParameter squared_distance: Set if the distance should be squared. :param nx.BoolParameter use_image_spacing: Set if image spacing should be used in computing distances. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Sin Image Filter -------------------- .. index:: pair: Filter Human Names; ITK Sin Image Filter .. index:: pair: Filter Class Names; ITKSinImageFilter .. _ITKSinImageFilter: .. py:class:: ITKSinImageFilter The computations are performed using std::sin(x). `Link to the full online documentation for ITKSinImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Sqrt Image Filter --------------------- .. index:: pair: Filter Human Names; ITK Sqrt Image Filter .. index:: pair: Filter Class Names; ITKSqrtImageFilter .. _ITKSqrtImageFilter: .. py:class:: ITKSqrtImageFilter The computations are performed using std::sqrt(x). `Link to the full online documentation for ITKSqrtImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Square Image Filter ----------------------- .. index:: pair: Filter Human Names; ITK Square Image Filter .. index:: pair: Filter Class Names; ITKSquareImageFilter .. _ITKSquareImageFilter: .. py:class:: ITKSquareImageFilter !` `_ `Link to the full online documentation for ITKSquareImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Tan Image Filter -------------------- .. index:: pair: Filter Human Names; ITK Tan Image Filter .. index:: pair: Filter Class Names; ITKTanImageFilter .. _ITKTanImageFilter: .. py:class:: ITKTanImageFilter The computations are performed using std::tan(x). `Link to the full online documentation for ITKTanImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Threshold Image Filter -------------------------- .. index:: pair: Filter Human Names; ITK Threshold Image Filter .. index:: pair: Filter Class Names; ITKThresholdImageFilter .. _ITKThresholdImageFilter: .. py:class:: ITKThresholdImageFilter ThresholdImageFilter sets image values to a user-specified "outside" value (by default, "black") if the image values are below, above, or between simple threshold values. `Link to the full online documentation for ITKThresholdImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Lower | lower | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Outside Value | outside_value | +------------------+---------------------------+ | Upper | upper | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, lower, output_array_name, outside_value, upper) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.Float64Parameter lower: Set/Get methods to set the lower threshold. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.Float64Parameter outside_value: The pixel type must support comparison operators. Set the 'outside' pixel value. The default value NumericTraits::ZeroValue() . :param nx.Float64Parameter upper: Set/Get methods to set the upper threshold. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Threshold Maximum Connected Components Image Filter ------------------------------------------------------- .. index:: pair: Filter Human Names; ITK Threshold Maximum Connected Components Image Filter .. index:: pair: Filter Class Names; ITKThresholdMaximumConnectedComponentsImageFilter .. _ITKThresholdMaximumConnectedComponentsImageFilter: .. py:class:: ITKThresholdMaximumConnectedComponentsImageFilter This method is based on Topological Stable State Thresholding to calculate the threshold set point. This method is particularly effective when there are a large number of objects in a microscopy image. Compiling in Debug mode and enable the debug flag for this filter to print debug information to see how the filter focuses in on a threshold value. Please see the Insight Journal's MICCAI 2005 workshop for a complete description. References are below. `Link to the full online documentation for ITKThresholdMaximumConnectedComponentsImageFilter `_ Mapping of UI display to python named argument +-------------------------------+-------------------------------+ | UI Display | Python Named Argument | +===============================+===============================+ | Input Cell Data | input_image_data_path | +-------------------------------+-------------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------------+-------------------------------+ | Inside Value | inside_value | +-------------------------------+-------------------------------+ | Minimum Object Size In Pixels | minimum_object_size_in_pixels | +-------------------------------+-------------------------------+ | Output Image Data Array | output_array_name | +-------------------------------+-------------------------------+ | Outside Value | outside_value | +-------------------------------+-------------------------------+ | Upper Boundary | upper_boundary | +-------------------------------+-------------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, inside_value, minimum_object_size_in_pixels, output_array_name, outside_value, upper_boundary) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.UInt8Parameter inside_value: The following Set/Get methods are for the binary threshold function. This class automatically calculates the lower threshold boundary. The upper threshold boundary, inside value, and outside value can be defined by the user, however the standard values are used as default if not set by the user. The default value of the: Inside value is the maximum pixel type intensity. Outside value is the minimum pixel type intensity. Upper threshold boundary is the maximum pixel type intensity. :param nx.UInt32Parameter minimum_object_size_in_pixels: The pixel type must support comparison operators. Set the minimum pixel area used to count objects on the image. Thus, only objects that have a pixel area greater than the minimum pixel area will be counted as an object in the optimization portion of this filter. Essentially, it eliminates noise from being counted as an object. The default value is zero. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :param nx.UInt8Parameter outside_value: The following Set/Get methods are for the binary threshold function. This class automatically calculates the lower threshold boundary. The upper threshold boundary, inside value, and outside value can be defined by the user, however the standard values are used as default if not set by the user. The default value of the: Inside value is the maximum pixel type intensity. Outside value is the minimum pixel type intensity. Upper threshold boundary is the maximum pixel type intensity. :param nx.Float64Parameter upper_boundary: The following Set/Get methods are for the binary threshold function. This class automatically calculates the lower threshold boundary. The upper threshold boundary, inside value, and outside value can be defined by the user, however the standard values are used as default if not set by the user. The default value of the: Inside value is the maximum pixel type intensity. Outside value is the minimum pixel type intensity. Upper threshold boundary is the maximum pixel type intensity. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Valued Regional Maxima Image Filter --------------------------------------- .. index:: pair: Filter Human Names; ITK Valued Regional Maxima Image Filter .. index:: pair: Filter Class Names; ITKValuedRegionalMaximaImageFilter .. _ITKValuedRegionalMaximaImageFilter: .. py:class:: ITKValuedRegionalMaximaImageFilter Regional maxima are flat zones surrounded by pixels of lower value. A completely flat image will be marked as a regional maxima by this filter. `Link to the full online documentation for ITKValuedRegionalMaximaImageFilter `_ Mapping of UI display to python named argument +----------------------------+---------------------------+ | UI Display | Python Named Argument | +============================+===========================+ | Fully Connected Components | fully_connected | +----------------------------+---------------------------+ | Input Cell Data | input_image_data_path | +----------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +----------------------------+---------------------------+ | Output Cell Data | output_array_name | +----------------------------+---------------------------+ .. py:method:: Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.BoolParameter fully_connected: Whether the connected components are defined strictly by face connectivity (False) or by face+edge+vertex connectivity (True). Default is FalseFor objects that are 1 pixel wide, use True. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Valued Regional Minima Image Filter --------------------------------------- .. index:: pair: Filter Human Names; ITK Valued Regional Minima Image Filter .. index:: pair: Filter Class Names; ITKValuedRegionalMinimaImageFilter .. _ITKValuedRegionalMinimaImageFilter: .. py:class:: ITKValuedRegionalMinimaImageFilter Regional minima are flat zones surrounded by pixels of higher value. A completely flat image will be marked as a regional minima by this filter. `Link to the full online documentation for ITKValuedRegionalMinimaImageFilter `_ Mapping of UI display to python named argument +----------------------------+---------------------------+ | UI Display | Python Named Argument | +============================+===========================+ | Fully Connected Components | fully_connected | +----------------------------+---------------------------+ | Input Cell Data | input_image_data_path | +----------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +----------------------------+---------------------------+ | Output Cell Data | output_array_name | +----------------------------+---------------------------+ .. py:method:: Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.BoolParameter fully_connected: Whether the connected components are defined strictly by face connectivity (False) or by face+edge+vertex connectivity (True). Default is FalseFor objects that are 1 pixel wide, use True. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK White Top Hat Image Filter ------------------------------ .. index:: pair: Filter Human Names; ITK White Top Hat Image Filter .. index:: pair: Filter Class Names; ITKWhiteTopHatImageFilter .. _ITKWhiteTopHatImageFilter: .. py:class:: ITKWhiteTopHatImageFilter Top-hats are described in Chapter 4.5 of Pierre Soille's book "Morphological Image Analysis: Principles and Applications", Second Edition, Springer, 2003. `Link to the full online documentation for ITKWhiteTopHatImageFilter `_ Mapping of UI display to python named argument +------------------+---------------------------+ | UI Display | Python Named Argument | +==================+===========================+ | Input Cell Data | input_image_data_path | +------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +------------------+---------------------------+ | Kernel Radius | kernel_radius | +------------------+---------------------------+ | Kernel Type | kernel_type_index | +------------------+---------------------------+ | Output Cell Data | output_array_name | +------------------+---------------------------+ | Safe Border | safe_border | +------------------+---------------------------+ .. py:method:: Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, safe_border) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.VectorUInt32Parameter kernel_radius: The radius of the kernel structuring element. :param nx.ChoicesParameter kernel_type_index: Set the kernel or structuring element used for the morphology. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array inside the same group as the input data. :param nx.BoolParameter safe_border: A safe border is added to input image to avoid borders effects and remove it once the closing is done :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult ` ITK Zero Crossing Image Filter ------------------------------ .. index:: pair: Filter Human Names; ITK Zero Crossing Image Filter .. index:: pair: Filter Class Names; ITKZeroCrossingImageFilter .. _ITKZeroCrossingImageFilter: .. py:class:: ITKZeroCrossingImageFilter Pixels closest to zero-crossings are labeled with a foreground value. All other pixels are marked with a background value. The algorithm works by detecting differences in sign among neighbors using city-block style connectivity (4-neighbors in 2d, 6-neighbors in 3d, etc.). `Link to the full online documentation for ITKZeroCrossingImageFilter `_ Mapping of UI display to python named argument +-------------------------+---------------------------+ | UI Display | Python Named Argument | +=========================+===========================+ | Background Value | background_value | +-------------------------+---------------------------+ | Foreground Value | foreground_value | +-------------------------+---------------------------+ | Input Cell Data | input_image_data_path | +-------------------------+---------------------------+ | Image Geometry | input_image_geometry_path | +-------------------------+---------------------------+ | Output Image Data Array | output_array_name | +-------------------------+---------------------------+ .. py:method:: Execute(data_structure, background_value, foreground_value, input_image_data_path, input_image_geometry_path, output_array_name) :param DataStructure data_structure: The DataStructure object that holds the data to be processed. :param nx.UInt8Parameter background_value: Set/Get the label value for non-zero-crossing pixels. :param nx.UInt8Parameter foreground_value: Set/Get the label value for zero-crossing pixels. :param nx.ArraySelectionParameter input_image_data_path: The image data that will be processed by this filter. :param nx.GeometrySelectionParameter input_image_geometry_path: Select the Image Geometry Group from the DataStructure. :param nx.DataObjectNameParameter output_array_name: The result of the processing will be stored in this Data Array. :return: Returns a :ref:`nx.IFilter.ExecuteResult ` object that holds any warnings and/or errors that were encountered during execution. :rtype: :ref:`nx.IFilter.ExecuteResult `