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:

import itkimageprocessing
# Instantiate and execute a filter from the module
result = itkimageprocessing.SomeFilterName.execute(...)

ITK Abs Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Acos Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Adaptive Histogram Equalization Image Filter

class ITKImageProcessing.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
Execute(data_structure, alpha, beta, input_image_data_path, input_image_geometry_path, output_array_name, radius)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • alpha (nx.Float32Parameter) – 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.

  • beta (nx.Float32Parameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • radius (nx.VectorUInt32Parameter) – Radius Dimensions XYZ

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Approximate Signed Distance Map Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, inside_value, output_array_name, outside_value)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Asin Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Atan Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Binary Contour Image Filter

class ITKImageProcessing.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
Execute(data_structure, background_value, foreground_value, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • background_value (nx.Float64Parameter) – Set/Get the background value used to mark the pixels not on the border of the objects.

  • foreground_value (nx.Float64Parameter) – Set/Get the foreground value used to identify the objects in the input and output images.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Binary Dilate Image Filter

class ITKImageProcessing.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
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)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • background_value (nx.Float64Parameter) – Set/Get the background value used to mark the pixels not on the border of the objects.

  • boundary_to_foreground (nx.BoolParameter) – Mark the boundary between foreground and background.

  • foreground_value (nx.Float64Parameter) – Set/Get the foreground value used to identify the objects in the input and output images.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • kernel_radius (nx.VectorUInt32Parameter) – The radius of the kernel structuring element.

  • kernel_type_index (nx.ChoicesParameter) – Set the kernel or structuring element used for the morphology.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Binary Erode Image Filter

class ITKImageProcessing.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
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)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • background_value (nx.Float64Parameter) – Set/Get the background value used to mark the pixels not on the border of the objects.

  • boundary_to_foreground (nx.BoolParameter) – Mark the boundary between foreground and background.

  • foreground_value (nx.Float64Parameter) – Set/Get the foreground value used to identify the objects in the input and output images.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • kernel_radius (nx.VectorUInt32Parameter) – The radius of the kernel structuring element.

  • kernel_type_index (nx.ChoicesParameter) – Set the kernel or structuring element used for the morphology.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Binary Morphological Closing Image Filter

class ITKImageProcessing.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
Execute(data_structure, foreground_value, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, safe_border)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • foreground_value (nx.Float64Parameter) – Set the value in the image to consider as ‘foreground’. Defaults to maximum value of InputPixelType.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • kernel_radius (nx.VectorUInt32Parameter) – The radius of the kernel structuring element.

  • kernel_type_index (nx.ChoicesParameter) – Set the kernel or structuring element used for the morphology.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • safe_border (nx.BoolParameter) – A safe border is added to input image to avoid borders effects and remove it once the closing is done

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Binary Morphological Opening Image Filter

class ITKImageProcessing.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
Execute(data_structure, background_value, foreground_value, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • background_value (nx.Float64Parameter) – Set the value in eroded part of the image. Defaults to zero

  • foreground_value (nx.Float64Parameter) – Set the value in the image to consider as ‘foreground’. Defaults to maximum value of PixelType.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • kernel_radius (nx.VectorUInt32Parameter) – The radius of the kernel structuring element.

  • kernel_type_index (nx.ChoicesParameter) – Set the kernel or structuring element used for the morphology.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Binary Opening By Reconstruction Image Filter

class ITKImageProcessing.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
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)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • background_value (nx.Float64Parameter) – Set the value in eroded part of the image. Defaults to zero

  • foreground_value (nx.Float64Parameter) – Set the value in the image to consider as ‘foreground’. Defaults to maximum value of PixelType.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • kernel_radius (nx.VectorUInt32Parameter) – The radius of the kernel structuring element.

  • kernel_type_index (nx.ChoicesParameter) – Set the kernel or structuring element used for the morphology.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Binary Projection Image Filter

class ITKImageProcessing.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 Cell Data

output_array_name

Projection Dimension

projection_dimension
Execute(data_structure, background_value, foreground_value, input_image_data_path, input_image_geometry_path, output_array_name, projection_dimension)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • background_value (nx.Float64Parameter) – 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<PixelType>::NonpositiveMin() .

  • foreground_value (nx.Float64Parameter) – Set the value in the image to consider as ‘foreground’. Defaults to maximum value of PixelType. Subclasses may alias this to DilateValue or ErodeValue.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • projection_dimension (nx.UInt32Parameter) – The dimension index to project. 0=Slowest moving dimension.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Binary Thinning Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Binary Threshold Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, inside_value, lower_threshold, output_array_name, outside_value, upper_threshold)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • inside_value (nx.UInt8Parameter) – Set the ‘inside’ pixel value. The default value NumericTraits<OutputPixelType>::max()

  • lower_threshold (nx.Float64Parameter) – The lower threshold that a pixel value could be and still be considered ‘Inside Value’

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • outside_value (nx.UInt8Parameter) – Set the ‘outside’ pixel value. The default value NumericTraits<OutputPixelType>::ZeroValue() .

  • upper_threshold (nx.Float64Parameter) – Set the thresholds. The default lower threshold is NumericTraits<InputPixelType>::NonpositiveMin() . The default upper threshold is NumericTraits<InputPixelType>::max . An exception is thrown if the lower threshold is greater than the upper threshold.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Black Top Hat Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, safe_border)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • kernel_radius (nx.VectorUInt32Parameter) – The radius of the kernel structuring element.

  • kernel_type_index (nx.ChoicesParameter) – Set the kernel or structuring element used for the morphology.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • safe_border (nx.BoolParameter) – A safe border is added to input image to avoid borders effects and remove it once the closing is done

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Closing By Reconstruction Image Filter

class ITKImageProcessing.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
Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, preserve_intensities)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • kernel_radius (nx.VectorUInt32Parameter) – The radius of the kernel structuring element.

  • kernel_type_index (nx.ChoicesParameter) – Set the kernel or structuring element used for the morphology.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • preserve_intensities (nx.BoolParameter) – 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.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Connected Component Image Filter

class ITKImageProcessing.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
Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Cos Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Curvature Anisotropic Diffusion Image Filter

class ITKImageProcessing.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
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)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • conductance_parameter (nx.Float64Parameter) – The conductance parameter controls the sensitivity of the conductance term in the basic anisotropic diffusion equation

  • conductance_scaling_update_interval (nx.UInt32Parameter) – The interval between conductance updates.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • number_of_iterations (nx.UInt32Parameter) – Specifies the number of iterations (time-step updates) that the solver will perform to produce a solution image

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

  • time_step (nx.Float64Parameter) – The time step to be used for each iteration.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Curvature Flow Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, number_of_iterations, output_array_name, time_step)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Danielsson Distance Map Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, input_is_binary, output_array_name, squared_distance, use_image_spacing)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • input_is_binary (nx.BoolParameter) – 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.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

  • squared_distance (nx.BoolParameter) – Set/Get if the distance should be squared.

  • use_image_spacing (nx.BoolParameter) – Set/Get if image spacing should be used in computing distances.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Dilate Object Morphology Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, object_value, output_array_name)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Discrete Gaussian Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, maximum_error, maximum_kernel_width, output_array_name, use_image_spacing, variance)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • maximum_error (nx.VectorFloat64Parameter) – 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.

  • maximum_kernel_width (nx.UInt32Parameter) – Set the kernel to be no wider than MaximumKernelWidth pixels, even if MaximumError demands it. The default is 32 pixels.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • use_image_spacing (nx.BoolParameter) – 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.

  • variance (nx.VectorFloat64Parameter) – 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.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Double Threshold Image Filter

class ITKImageProcessing.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
Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, inside_value, output_array_name, outside_value, threshold1, threshold2, threshold3, threshold4)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • inside_value (nx.UInt8Parameter) – Set the ‘inside’ pixel value. The default value NumericTraits<OutputPixelType>::max()

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

  • outside_value (nx.UInt8Parameter) – Set the ‘outside’ pixel value. The default value NumericTraits<OutputPixelType>::ZeroValue() .

  • threshold1 (nx.Float64Parameter) – Set the thresholds. Four thresholds should be specified. The two lower thresholds default to NumericTraits<InputPixelType>::NonpositiveMin() . The two upper thresholds default NumericTraits<InputPixelType>::max . Threshold1 <= Threshold2 <= Threshold3 <= Threshold4.

  • threshold2 (nx.Float64Parameter) – Set the thresholds. Four thresholds should be specified. The two lower thresholds default to NumericTraits<InputPixelType>::NonpositiveMin() . The two upper thresholds default NumericTraits<InputPixelType>::max . Threshold1 <= Threshold2 <= Threshold3 <= Threshold4.

  • threshold3 (nx.Float64Parameter) – Set the thresholds. Four thresholds should be specified. The two lower thresholds default to NumericTraits<InputPixelType>::NonpositiveMin() . The two upper thresholds default NumericTraits<InputPixelType>::max . Threshold1 <= Threshold2 <= Threshold3 <= Threshold4.

  • threshold4 (nx.Float64Parameter) – Set the thresholds. Four thresholds should be specified. The two lower thresholds default to NumericTraits<InputPixelType>::NonpositiveMin() . The two upper thresholds default NumericTraits<InputPixelType>::max . Threshold1 <= Threshold2 <= Threshold3 <= Threshold4.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Erode Object Morphology Image Filter

class ITKImageProcessing.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
Execute(data_structure, background_value, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, object_value, output_array_name)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Exp Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Exp Negative Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Gradient Anisotropic Diffusion Image Filter

class ITKImageProcessing.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
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)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • conductance_parameter (nx.Float64Parameter) – The conductance parameter controls the sensitivity of the conductance term in the basic anisotropic diffusion equation

  • conductance_scaling_update_interval (nx.UInt32Parameter) – The interval between conductance updates.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • number_of_iterations (nx.UInt32Parameter) – Specifies the number of iterations (time-step updates) that the solver will perform to produce a solution image

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

  • time_step (nx.Float64Parameter) – The time step to be used for each iteration.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Gradient Magnitude Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name, use_image_spacing)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • use_image_spacing (nx.BoolParameter) – 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.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Gradient Magnitude Recursive Gaussian Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, normalize_across_scale, output_array_name, sigma)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • normalize_across_scale (nx.BoolParameter) – Set/Get the normalization factor that will be used for the Gaussian. RecursiveGaussianImageFilter::SetNormalizeAcrossScale

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

  • sigma (nx.Float64Parameter) – Set/Get Sigma value. Sigma is measured in the units of image spacing.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Grayscale Dilate Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Grayscale Erode Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Grayscale Fillhole Image Filter

class ITKImageProcessing.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
Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Grayscale Grind Peak Image Filter

class ITKImageProcessing.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
Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Grayscale Morphological Closing Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, safe_border)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • kernel_radius (nx.VectorUInt32Parameter) – The radius of the kernel structuring element.

  • kernel_type_index (nx.ChoicesParameter) – Set the kernel or structuring element used for the morphology.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • safe_border (nx.BoolParameter) – A safe border is added to input image to avoid borders effects and remove it once the closing is done

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Grayscale Morphological Opening Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, safe_border)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • kernel_radius (nx.VectorUInt32Parameter) – The radius of the kernel structuring element.

  • kernel_type_index (nx.ChoicesParameter) – Set the kernel or structuring element used for the morphology.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • safe_border (nx.BoolParameter) – A safe border is added to input image to avoid borders effects and remove it once the closing is done

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK H Convex Image Filter

class ITKImageProcessing.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
Execute(data_structure, fully_connected, height, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • fully_connected (nx.BoolParameter) – 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.

  • height (nx.Float64Parameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK H Maxima Image Filter

class ITKImageProcessing.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
Execute(data_structure, height, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • height (nx.Float64Parameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK H Minima Image Filter

class ITKImageProcessing.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
Execute(data_structure, fully_connected, height, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • fully_connected (nx.BoolParameter) – 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.

  • height (nx.Float64Parameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

Read Image (ITK)

class ITKImageProcessing.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 Origin

change_origin

Set Spacing

change_spacing

File

file_name

Created Cell Data

image_data_array_name

Length Unit

length_unit_index

Origin (Physical Units)

origin

Created Image Geometry

output_geometry_path

Spacing (Physical Units)

spacing
Execute(data_structure, cell_attribute_matrix_name, center_origin, change_origin, change_spacing, file_name, image_data_array_name, length_unit_index, origin, output_geometry_path, spacing)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

Write Image (ITK)

class ITKImageProcessing.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
Execute(data_structure, file_name, image_array_path, index_offset, input_image_geometry_path, plane_index)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

Read Fiji Montage (ITK)

class ITKImageProcessing.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

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

Fiji Configuration File

input_file

Length Unit

length_unit_index

Origin

origin

Parent Imported Images Under a DataGroup

parent_data_group
Execute(data_structure, cell_attribute_matrix_name, change_origin, color_weights, convert_to_gray_scale, data_container_path, data_group_name, image_data_array_name, input_file, length_unit_index, origin, parent_data_group)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • cell_attribute_matrix_name (nx.StringParameter) – The name of the Cell Attribute Matrix

  • change_origin (nx.BoolParameter) – Set the origin of the mosaic to a user defined value

  • color_weights (nx.VectorFloat32Parameter) – The luminosity values for the conversion

  • convert_to_gray_scale (nx.BoolParameter) – The filter will show an error if the images are already in grayscale format

  • data_container_path (nx.StringParameter) – A prefix that can be used for each Image Geometry

  • data_group_name (nx.StringParameter) – Name of the overarching parent DataGroup

  • image_data_array_name (nx.StringParameter) – The name of the import image data

  • input_file (nx.FileSystemPathParameter) – This is the configuration file in the same directory as all of the identified geometries

  • length_unit_index (nx.ChoicesParameter) – The length unit that will be set into the created image geometry

  • origin (nx.VectorFloat32Parameter) – The new origin of the mosaic

  • parent_data_group (nx.BoolParameter) – Create a new DataGroup to hold the imported images

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

Read Images [3D Stack] (ITK)

class ITKImageProcessing.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.

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

Color Weighting

color_weights

Convert To GrayScale

convert_to_gray_scale

Created Image Data

image_data_array_name

Optional Slice Operations

image_transform_index

Input File List

input_file_list_object

Origin

origin

Created Image Geometry

output_image_geometry_path

Spacing

spacing
Execute(data_structure, cell_attribute_matrix_name, color_weights, convert_to_gray_scale, image_data_array_name, image_transform_index, input_file_list_object, origin, output_image_geometry_path, spacing)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Intensity Windowing Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name, output_maximum, output_minimum, window_maximum, window_minimum)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • output_maximum (nx.Float64Parameter) – Set/Get the values of the maximum and minimum intensities of the output image.

  • output_minimum (nx.Float64Parameter) – Set/Get the values of the maximum and minimum intensities of the output image.

  • window_maximum (nx.Float64Parameter) – Set/Get the values of the maximum and minimum intensities of the input intensity window.

  • window_minimum (nx.Float64Parameter) – Set/Get the values of the maximum and minimum intensities of the input intensity window.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Invert Intensity Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, maximum, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • maximum (nx.Float64Parameter) – Set/Get the maximum intensity value for the inversion.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Iso Contour Distance Image Filter

class ITKImageProcessing.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
Execute(data_structure, far_value, input_image_data_path, input_image_geometry_path, level_set_value, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • far_value (nx.Float64Parameter) – Set/Get the value of the level set to be located. The default value is 0.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • level_set_value (nx.Float64Parameter) – Set/Get the value of the level set to be located. The default value is 0.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Label Contour Image Filter

class ITKImageProcessing.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
Execute(data_structure, background_value, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • background_value (nx.Float64Parameter) – Set/Get the background value used to identify the objects and mark the pixels not on the border of the objects.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Laplacian Recursive Gaussian Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, normalize_across_scale, output_array_name, sigma)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • normalize_across_scale (nx.BoolParameter) – Define which normalization factor will be used for the Gaussian. See RecursiveGaussianImageFilter::SetNormalizeAcrossScale

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

  • sigma (nx.Float64Parameter) – Set/Get Sigma value. Sigma is measured in the units of image spacing.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Log10 Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Log Image Filter

class ITKImageProcessing.ITKLogImageFilter

!` <Images/ITKLogImageFilter.png>`_

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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Mask Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, mask_image_data_path, output_array_name, outside_value)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • mask_image_data_path (nx.ArraySelectionParameter) – The path to the image data to be used as the mask (should be the same size as the input image)

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • outside_value (nx.Float64Parameter) – Method to explicitly set the outside value of the mask.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Median Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name, radius)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK MHA File Reader

class ITKImageProcessing.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
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)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • apply_image_transformation (nx.BoolParameter) – When true, the transformation matrix found in the image’s header metadata will be applied to the created image geometry.

  • cell_attribute_matrix_name (nx.DataObjectNameParameter) – The name of the created cell attribute matrix

  • file_name (nx.FileSystemPathParameter) – The input .mha file that will be read.

  • image_data_array_name (nx.DataObjectNameParameter) – The name of the created image data array. Will be stored in the created Cell Attribute Matrix

  • interpolation_type_index (nx.ChoicesParameter) – The type of interpolation algorithm that is used. 0=NearestNeighbor, 1=Linear

  • output_geometry_path (nx.DataGroupCreationParameter) – The path to the created Image Geometry

  • output_transformation_matrix_path (nx.ArrayCreationParameter) – The path to the transformation matrix data array

  • save_image_transformation (nx.BoolParameter) – When true, the transformation matrix found in the image’s header metadata will be saved as a data array in the created image geometry.

  • transpose_transform_matrix (nx.BoolParameter) – When true, the transformation matrix found in the image’s header metadata will be transposed before use.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Min Max Curvature Flow Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, number_of_iterations, output_array_name, stencil_radius, time_step)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • number_of_iterations (nx.UInt32Parameter) – Specifies the number of iterations (time-step updates) that the solver will perform to produce a solution image

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

  • stencil_radius (nx.Int32Parameter) – Set/Get the stencil radius.

  • time_step (nx.Float64Parameter) – The time step to be used for each iteration.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Morphological Gradient Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Morphological Watershed Image Filter

class ITKImageProcessing.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
Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, level, mark_watershed_line, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • level (nx.Float64Parameter) – Set the ‘level’ variable to the filter

  • mark_watershed_line (nx.BoolParameter) – 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.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Normalize Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Not Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Opening By Reconstruction Image Filter

class ITKImageProcessing.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
Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, preserve_intensities)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • kernel_radius (nx.VectorUInt32Parameter) – The radius of the kernel structuring element.

  • kernel_type_index (nx.ChoicesParameter) – Set the kernel or structuring element used for the morphology.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • preserve_intensities (nx.BoolParameter) – 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.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Otsu Multiple Thresholds Image Filter

class ITKImageProcessing.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
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)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • label_offset (nx.UInt8Parameter) – Set/Get the offset which labels have to start from. Default is 0.

  • number_of_histogram_bins (nx.UInt32Parameter) – Set/Get the number of histogram bins. Default is 128.

  • number_of_thresholds (nx.UInt8Parameter) – Set/Get the number of thresholds. Default is 1.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • return_bin_midpoint (nx.BoolParameter) – Should the threshold value be mid-point of the bin or the maximum? Default is to return bin maximum.

  • valley_emphasis (nx.BoolParameter) – Set/Get the use of valley emphasis. Default is false.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Regional Maxima Image Filter

class ITKImageProcessing.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
Execute(data_structure, background_value, flat_is_maxima, foreground_value, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • background_value (nx.Float64Parameter) – Set/Get the value used as ‘background’ in the output image. Defaults to NumericTraits<PixelType>::NonpositiveMin() .

  • flat_is_maxima (nx.BoolParameter) – Set/Get whether a flat image must be considered as a maxima or not. Defaults to true.

  • foreground_value (nx.Float64Parameter) – Set/Get the value in the output image to consider as ‘foreground’. Defaults to maximum value of PixelType.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Regional Minima Image Filter

class ITKImageProcessing.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
Execute(data_structure, background_value, flat_is_minima, foreground_value, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • background_value (nx.Float64Parameter) – Set/Get the value used as ‘background’ in the output image. Defaults to NumericTraits<PixelType>::NonpositiveMin() .

  • flat_is_minima (nx.BoolParameter) – Set/Get whether a flat image must be considered as a minima or not. Defaults to true.

  • foreground_value (nx.Float64Parameter) – Set/Get the value in the output image to consider as ‘foreground’. Defaults to maximum value of PixelType.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Relabel Component Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, minimum_object_size, output_array_name, sort_by_object_size)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • minimum_object_size (nx.UInt64Parameter) – 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.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • sort_by_object_size (nx.BoolParameter) – Controls whether the object labels are sorted by size. If false, initial order of labels is kept.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Rescale Intensity Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name, output_maximum, output_minimum)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Sigmoid Image Filter

class ITKImageProcessing.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
Execute(data_structure, alpha, beta, input_image_data_path, input_image_geometry_path, output_array_name, output_maximum, output_minimum)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Signed Danielsson Distance Map Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, inside_is_positive, output_array_name, squared_distance, use_image_spacing)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • inside_is_positive (nx.BoolParameter) – Set if the inside represents positive values in the signed distance map. By convention ON pixels are treated as inside pixels.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

  • squared_distance (nx.BoolParameter) – Set if the distance should be squared.

  • use_image_spacing (nx.BoolParameter) – Set if image spacing should be used in computing distances.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Signed Maurer Distance Map Image Filter

class ITKImageProcessing.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
Execute(data_structure, background_value, input_image_data_path, input_image_geometry_path, inside_is_positive, output_array_name, squared_distance, use_image_spacing)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • background_value (nx.Float64Parameter) – Set the background value which defines the object. Usually this value is = 0.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • inside_is_positive (nx.BoolParameter) – Set if the inside represents positive values in the signed distance map. By convention ON pixels are treated as inside pixels.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • squared_distance (nx.BoolParameter) – Set if the distance should be squared.

  • use_image_spacing (nx.BoolParameter) – Set if image spacing should be used in computing distances.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Sin Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Sqrt Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Square Image Filter

class ITKImageProcessing.ITKSquareImageFilter

!` <Images/ITKSquareImageFilter.png>`_

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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Tan Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Threshold Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, lower, output_array_name, outside_value, upper)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • lower (nx.Float64Parameter) – Set/Get methods to set the lower threshold.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • outside_value (nx.Float64Parameter) – The pixel type must support comparison operators. Set the ‘outside’ pixel value. The default value NumericTraits<PixelType>::ZeroValue() .

  • upper (nx.Float64Parameter) – Set/Get methods to set the upper threshold.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Threshold Maximum Connected Components Image Filter

class ITKImageProcessing.ITKThresholdMaximumConnectedComponentsImageFilter

parThis 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
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)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • inside_value (nx.UInt8Parameter) – 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.

  • minimum_object_size_in_pixels (nx.UInt32Parameter) – 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.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array.

  • outside_value (nx.UInt8Parameter) – 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.

  • upper_boundary (nx.Float64Parameter) – 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.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Valued Regional Maxima Image Filter

class ITKImageProcessing.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
Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Valued Regional Minima Image Filter

class ITKImageProcessing.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
Execute(data_structure, fully_connected, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • fully_connected (nx.BoolParameter) – 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.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK White Top Hat Image Filter

class ITKImageProcessing.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
Execute(data_structure, input_image_data_path, input_image_geometry_path, kernel_radius, kernel_type_index, output_array_name, safe_border)
Parameters:

  • data_structure (DataStructure) – The DataStructure object that holds the data to be processed.

  • input_image_data_path (nx.ArraySelectionParameter) – The image data that will be processed by this filter.

  • input_image_geometry_path (nx.GeometrySelectionParameter) – Select the Image Geometry Group from the DataStructure.

  • kernel_radius (nx.VectorUInt32Parameter) – The radius of the kernel structuring element.

  • kernel_type_index (nx.ChoicesParameter) – Set the kernel or structuring element used for the morphology.

  • output_array_name (nx.DataObjectNameParameter) – The result of the processing will be stored in this Data Array inside the same group as the input data.

  • safe_border (nx.BoolParameter) – A safe border is added to input image to avoid borders effects and remove it once the closing is done

Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult

ITK Zero Crossing Image Filter

class ITKImageProcessing.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
Execute(data_structure, background_value, foreground_value, input_image_data_path, input_image_geometry_path, output_array_name)
Parameters:
Returns:

Returns a nx.IFilter.ExecuteResult object that holds any warnings and/or errors that were encountered during execution.

Return type:

nx.IFilter.ExecuteResult