interfaces.semtools.filtering.featuredetection¶
CannyEdge¶
Wraps the executable command `` CannyEdge ``.
title: Canny Edge Detection
category: Filtering.FeatureDetection
description: Get the distance from a voxel to the nearest voxel of a given tissue type.
version: 0.1.0.(alpha)
documentation-url: http:://www.na-mic.org/
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This tool was written by Hans J. Johnson.
Inputs:
[Optional]
inputVolume: (an existing file name)
Required: input tissue label image
argument: ``--inputVolume %s``
variance: (a float)
Variance and Maximum error are used in the Gaussian smoothing of the
input image. See itkDiscreteGaussianImageFilter for information on
these parameters.
argument: ``--variance %f``
upperThreshold: (a float)
Threshold is the lowest allowed value in the output image. Its data
type is the same as the data type of the output image. Any values
below the Threshold level will be replaced with the OutsideValue
parameter value, whose default is zero.
argument: ``--upperThreshold %f``
lowerThreshold: (a float)
Threshold is the lowest allowed value in the output image. Its data
type is the same as the data type of the output image. Any values
below the Threshold level will be replaced with the OutsideValue
parameter value, whose default is zero.
argument: ``--lowerThreshold %f``
outputVolume: (a boolean or a file name)
Required: output image
argument: ``--outputVolume %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
Required: output image
CannySegmentationLevelSetImageFilter¶
Wraps the executable command `` CannySegmentationLevelSetImageFilter ``.
title: Canny Level Set Image Filter
category: Filtering.FeatureDetection
description: The CannySegmentationLevelSet is commonly used to refine a manually generated manual mask.
version: 0.3.0
license: CC
contributor: Regina Kim
acknowledgements: This command module was derived from Insight/Examples/Segmentation/CannySegmentationLevelSetImageFilter.cxx (copyright) Insight Software Consortium. See http://wiki.na-mic.org/Wiki/index.php/Slicer3:Execution_Model_Documentation for more detailed descriptions.
Inputs:
[Optional]
inputVolume: (an existing file name)
argument: ``--inputVolume %s``
initialModel: (an existing file name)
argument: ``--initialModel %s``
outputVolume: (a boolean or a file name)
argument: ``--outputVolume %s``
outputSpeedVolume: (a boolean or a file name)
argument: ``--outputSpeedVolume %s``
cannyThreshold: (a float)
Canny Threshold Value
argument: ``--cannyThreshold %f``
cannyVariance: (a float)
Canny variance
argument: ``--cannyVariance %f``
advectionWeight: (a float)
Controls the smoothness of the resulting mask, small number are more
smooth, large numbers allow more sharp corners.
argument: ``--advectionWeight %f``
initialModelIsovalue: (a float)
The identification of the input model iso-surface. (for a binary
image with 0s and 1s use 0.5) (for a binary image with 0s and 255's
use 127.5).
argument: ``--initialModelIsovalue %f``
maxIterations: (an integer (int or long))
The
argument: ``--maxIterations %d``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
outputSpeedVolume: (an existing file name)
DilateImage¶
Wraps the executable command `` DilateImage ``.
title: Dilate Image
category: Filtering.FeatureDetection
description: Uses mathematical morphology to dilate the input images.
version: 0.1.0.$Revision: 1 $(alpha)
documentation-url: http:://www.na-mic.org/
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This tool was developed by Mark Scully and Jeremy Bockholt.
Inputs:
[Optional]
inputVolume: (an existing file name)
Required: input image
argument: ``--inputVolume %s``
inputMaskVolume: (an existing file name)
Required: input brain mask image
argument: ``--inputMaskVolume %s``
inputRadius: (an integer (int or long))
Required: input neighborhood radius
argument: ``--inputRadius %d``
outputVolume: (a boolean or a file name)
Required: output image
argument: ``--outputVolume %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
Required: output image
DilateMask¶
Wraps the executable command `` DilateMask ``.
title: Dilate Image
category: Filtering.FeatureDetection
description: Uses mathematical morphology to dilate the input images.
version: 0.1.0.$Revision: 1 $(alpha)
documentation-url: http:://www.na-mic.org/
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This tool was developed by Mark Scully and Jeremy Bockholt.
Inputs:
[Optional]
inputVolume: (an existing file name)
Required: input image
argument: ``--inputVolume %s``
inputBinaryVolume: (an existing file name)
Required: input brain mask image
argument: ``--inputBinaryVolume %s``
sizeStructuralElement: (an integer (int or long))
size of structural element. sizeStructuralElement=1 means that 3x3x3
structuring element for 3D
argument: ``--sizeStructuralElement %d``
lowerThreshold: (a float)
Required: lowerThreshold value
argument: ``--lowerThreshold %f``
outputVolume: (a boolean or a file name)
Required: output image
argument: ``--outputVolume %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
Required: output image
DistanceMaps¶
Wraps the executable command `` DistanceMaps ``.
title: Mauerer Distance
category: Filtering.FeatureDetection
description: Get the distance from a voxel to the nearest voxel of a given tissue type.
version: 0.1.0.$Revision: 1 $(alpha)
documentation-url: http:://www.na-mic.org/
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This tool was developed by Mark Scully and Jeremy Bockholt.
Inputs:
[Optional]
inputLabelVolume: (an existing file name)
Required: input tissue label image
argument: ``--inputLabelVolume %s``
inputMaskVolume: (an existing file name)
Required: input brain mask image
argument: ``--inputMaskVolume %s``
inputTissueLabel: (an integer (int or long))
Required: input integer value of tissue type used to calculate
distance
argument: ``--inputTissueLabel %d``
outputVolume: (a boolean or a file name)
Required: output image
argument: ``--outputVolume %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
Required: output image
DumpBinaryTrainingVectors¶
Wraps the executable command `` DumpBinaryTrainingVectors ``.
title: Erode Image
category: Filtering.FeatureDetection
description: Uses mathematical morphology to erode the input images.
version: 0.1.0.$Revision: 1 $(alpha)
documentation-url: http:://www.na-mic.org/
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This tool was developed by Mark Scully and Jeremy Bockholt.
Inputs:
[Optional]
inputHeaderFilename: (an existing file name)
Required: input header file name
argument: ``--inputHeaderFilename %s``
inputVectorFilename: (an existing file name)
Required: input vector filename
argument: ``--inputVectorFilename %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
None
ErodeImage¶
Wraps the executable command `` ErodeImage ``.
title: Erode Image
category: Filtering.FeatureDetection
description: Uses mathematical morphology to erode the input images.
version: 0.1.0.$Revision: 1 $(alpha)
documentation-url: http:://www.na-mic.org/
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This tool was developed by Mark Scully and Jeremy Bockholt.
Inputs:
[Optional]
inputVolume: (an existing file name)
Required: input image
argument: ``--inputVolume %s``
inputMaskVolume: (an existing file name)
Required: input brain mask image
argument: ``--inputMaskVolume %s``
inputRadius: (an integer (int or long))
Required: input neighborhood radius
argument: ``--inputRadius %d``
outputVolume: (a boolean or a file name)
Required: output image
argument: ``--outputVolume %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
Required: output image
FlippedDifference¶
Wraps the executable command `` FlippedDifference ``.
title: Flip Image
category: Filtering.FeatureDetection
description: Difference between an image and the axially flipped version of that image.
version: 0.1.0.$Revision: 1 $(alpha)
documentation-url: http:://www.na-mic.org/
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This tool was developed by Mark Scully and Jeremy Bockholt.
Inputs:
[Optional]
inputVolume: (an existing file name)
Required: input image
argument: ``--inputVolume %s``
inputMaskVolume: (an existing file name)
Required: input brain mask image
argument: ``--inputMaskVolume %s``
outputVolume: (a boolean or a file name)
Required: output image
argument: ``--outputVolume %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
Required: output image
GenerateBrainClippedImage¶
Wraps the executable command `` GenerateBrainClippedImage ``.
title: GenerateBrainClippedImage
category: Filtering.FeatureDetection
description: Automatic FeatureImages using neural networks
version: 1.0
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: Eun Young Kim
Inputs:
[Optional]
inputImg: (an existing file name)
input volume 1, usally t1 image
argument: ``--inputImg %s``
inputMsk: (an existing file name)
input volume 2, usally t2 image
argument: ``--inputMsk %s``
outputFileName: (a boolean or a file name)
(required) output file name
argument: ``--outputFileName %s``
numberOfThreads: (an integer (int or long))
Explicitly specify the maximum number of threads to use.
argument: ``--numberOfThreads %d``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputFileName: (an existing file name)
(required) output file name
GenerateSummedGradientImage¶
Wraps the executable command `` GenerateSummedGradientImage ``.
title: GenerateSummedGradient
category: Filtering.FeatureDetection
description: Automatic FeatureImages using neural networks
version: 1.0
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: Greg Harris, Eun Young Kim
Inputs:
[Optional]
inputVolume1: (an existing file name)
input volume 1, usally t1 image
argument: ``--inputVolume1 %s``
inputVolume2: (an existing file name)
input volume 2, usally t2 image
argument: ``--inputVolume2 %s``
outputFileName: (a boolean or a file name)
(required) output file name
argument: ``--outputFileName %s``
MaximumGradient: (a boolean)
If set this flag, it will compute maximum gradient between two input
volumes instead of sum of it.
argument: ``--MaximumGradient ``
numberOfThreads: (an integer (int or long))
Explicitly specify the maximum number of threads to use.
argument: ``--numberOfThreads %d``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputFileName: (an existing file name)
(required) output file name
GenerateTestImage¶
Wraps the executable command `` GenerateTestImage ``.
title: DownSampleImage
category: Filtering.FeatureDetection
description: Down sample image for testing
version: 1.0
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: Eun Young Kim
Inputs:
[Optional]
inputVolume: (an existing file name)
input volume 1, usally t1 image
argument: ``--inputVolume %s``
outputVolume: (a boolean or a file name)
(required) output file name
argument: ``--outputVolume %s``
lowerBoundOfOutputVolume: (a float)
argument: ``--lowerBoundOfOutputVolume %f``
upperBoundOfOutputVolume: (a float)
argument: ``--upperBoundOfOutputVolume %f``
outputVolumeSize: (a float)
output Volume Size
argument: ``--outputVolumeSize %f``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
(required) output file name
GradientAnisotropicDiffusionImageFilter¶
Wraps the executable command `` GradientAnisotropicDiffusionImageFilter ``.
title: GradientAnisopropicDiffusionFilter
category: Filtering.FeatureDetection
description: Image Smoothing using Gradient Anisotropic Diffuesion Filer
contributor: This tool was developed by Eun Young Kim by modifying ITK Example
Inputs:
[Optional]
inputVolume: (an existing file name)
Required: input image
argument: ``--inputVolume %s``
numberOfIterations: (an integer (int or long))
Optional value for number of Iterations
argument: ``--numberOfIterations %d``
timeStep: (a float)
Time step for diffusion process
argument: ``--timeStep %f``
conductance: (a float)
Conductance for diffusion process
argument: ``--conductance %f``
outputVolume: (a boolean or a file name)
Required: output image
argument: ``--outputVolume %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
Required: output image
HammerAttributeCreator¶
Wraps the executable command `` HammerAttributeCreator ``.
title: HAMMER Feature Vectors
category: Filtering.FeatureDetection
description: Create the feature vectors used by HAMMER.
version: 0.1.0.$Revision: 1 $(alpha)
documentation-url: http:://www.na-mic.org/
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This was extracted from the Hammer Registration source code, and wrapped up by Hans J. Johnson.
Inputs:
[Optional]
Scale: (an integer (int or long))
Determine Scale of Ball
argument: ``--Scale %d``
Strength: (a float)
Determine Strength of Edges
argument: ``--Strength %f``
inputGMVolume: (an existing file name)
Required: input grey matter posterior image
argument: ``--inputGMVolume %s``
inputWMVolume: (an existing file name)
Required: input white matter posterior image
argument: ``--inputWMVolume %s``
inputCSFVolume: (an existing file name)
Required: input CSF posterior image
argument: ``--inputCSFVolume %s``
outputVolumeBase: (a unicode string)
Required: output image base name to be appended for each feature
vector.
argument: ``--outputVolumeBase %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
None
NeighborhoodMean¶
Wraps the executable command `` NeighborhoodMean ``.
title: Neighborhood Mean
category: Filtering.FeatureDetection
description: Calculates the mean, for the given neighborhood size, at each voxel of the T1, T2, and FLAIR.
version: 0.1.0.$Revision: 1 $(alpha)
documentation-url: http:://www.na-mic.org/
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This tool was developed by Mark Scully and Jeremy Bockholt.
Inputs:
[Optional]
inputVolume: (an existing file name)
Required: input image
argument: ``--inputVolume %s``
inputMaskVolume: (an existing file name)
Required: input brain mask image
argument: ``--inputMaskVolume %s``
inputRadius: (an integer (int or long))
Required: input neighborhood radius
argument: ``--inputRadius %d``
outputVolume: (a boolean or a file name)
Required: output image
argument: ``--outputVolume %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
Required: output image
NeighborhoodMedian¶
Wraps the executable command `` NeighborhoodMedian ``.
title: Neighborhood Median
category: Filtering.FeatureDetection
description: Calculates the median, for the given neighborhood size, at each voxel of the input image.
version: 0.1.0.$Revision: 1 $(alpha)
documentation-url: http:://www.na-mic.org/
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This tool was developed by Mark Scully and Jeremy Bockholt.
Inputs:
[Optional]
inputVolume: (an existing file name)
Required: input image
argument: ``--inputVolume %s``
inputMaskVolume: (an existing file name)
Required: input brain mask image
argument: ``--inputMaskVolume %s``
inputRadius: (an integer (int or long))
Required: input neighborhood radius
argument: ``--inputRadius %d``
outputVolume: (a boolean or a file name)
Required: output image
argument: ``--outputVolume %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
Required: output image
STAPLEAnalysis¶
Wraps the executable command `` STAPLEAnalysis ``.
title: Dilate Image
category: Filtering.FeatureDetection
description: Uses mathematical morphology to dilate the input images.
version: 0.1.0.$Revision: 1 $(alpha)
documentation-url: http:://www.na-mic.org/
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This tool was developed by Mark Scully and Jeremy Bockholt.
Inputs:
[Optional]
inputDimension: (an integer (int or long))
Required: input image Dimension 2 or 3
argument: ``--inputDimension %d``
inputLabelVolume: (a list of items which are an existing file name)
Required: input label volume
argument: ``--inputLabelVolume %s...``
outputVolume: (a boolean or a file name)
Required: output image
argument: ``--outputVolume %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
Required: output image
TextureFromNoiseImageFilter¶
Wraps the executable command `` TextureFromNoiseImageFilter ``.
title: TextureFromNoiseImageFilter
category: Filtering.FeatureDetection
description: Calculate the local noise in an image.
version: 0.1.0.$Revision: 1 $(alpha)
documentation-url: http:://www.na-mic.org/
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This tool was developed by Eunyoung Regina Kim
Inputs:
[Optional]
inputVolume: (an existing file name)
Required: input image
argument: ``--inputVolume %s``
inputRadius: (an integer (int or long))
Required: input neighborhood radius
argument: ``--inputRadius %d``
outputVolume: (a boolean or a file name)
Required: output image
argument: ``--outputVolume %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputVolume: (an existing file name)
Required: output image
TextureMeasureFilter¶
Wraps the executable command `` TextureMeasureFilter ``.
title: Canny Level Set Image Filter
category: Filtering.FeatureDetection
description: The CannySegmentationLevelSet is commonly used to refine a manually generated manual mask.
version: 0.3.0
license: CC
contributor: Regina Kim
acknowledgements: This command module was derived from Insight/Examples/Segmentation/CannySegmentationLevelSetImageFilter.cxx (copyright) Insight Software Consortium. See http://wiki.na-mic.org/Wiki/index.php/Slicer3:Execution_Model_Documentation for more detailed descriptions.
Inputs:
[Optional]
inputVolume: (an existing file name)
argument: ``--inputVolume %s``
inputMaskVolume: (an existing file name)
argument: ``--inputMaskVolume %s``
distance: (an integer (int or long))
argument: ``--distance %d``
insideROIValue: (a float)
argument: ``--insideROIValue %f``
outputFilename: (a boolean or a file name)
argument: ``--outputFilename %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
outputFilename: (an existing file name)