interfaces.semtools.utilities.brains¶
BRAINSAlignMSP¶
Wraps the executable command `` BRAINSAlignMSP ``.
title: Align Mid Saggital Brain (BRAINS)
category: Utilities.BRAINS
description: Resample an image into ACPC alignement ACPCDetect
Inputs:
[Optional]
inputVolume: (a pathlike object or string representing an existing
file)
, The Image to be resampled,
argument: ``--inputVolume %s``
OutputresampleMSP: (a boolean or a pathlike object or string
representing a file)
, The image to be output.,
argument: ``--OutputresampleMSP %s``
verbose: (a boolean)
, Show more verbose output,
argument: ``--verbose ``
resultsDir: (a boolean or a pathlike object or string representing a
directory)
, The directory for the results to be written.,
argument: ``--resultsDir %s``
writedebuggingImagesLevel: (an integer (int or long))
, This flag controls if debugging images are produced. By default
value of 0 is no images. Anything greater than zero will be
increasing level of debugging images.,
argument: ``--writedebuggingImagesLevel %d``
mspQualityLevel: (an integer (int or long))
, Flag cotrols how agressive the MSP is estimated. 0=quick estimate
(9 seconds), 1=normal estimate (11 seconds), 2=great estimate (22
seconds), 3=best estimate (58 seconds).,
argument: ``--mspQualityLevel %d``
rescaleIntensities: (a boolean)
, Flag to turn on rescaling image intensities on input.,
argument: ``--rescaleIntensities ``
trimRescaledIntensities: (a float)
, Turn on clipping the rescaled image one-tailed on input. Units of
standard deviations above the mean. Very large values are very
permissive. Non-positive value turns clipping off. Defaults to
removing 0.00001 of a normal tail above the mean.,
argument: ``--trimRescaledIntensities %f``
rescaleIntensitiesOutputRange: (a list of items which are an integer
(int or long))
, This pair of integers gives the lower and upper bounds on the
signal portion of the output image. Out-of-field voxels are taken
from BackgroundFillValue.,
argument: ``--rescaleIntensitiesOutputRange %s``
BackgroundFillValue: (a unicode string)
Fill the background of image with specified short int value. Enter
number or use BIGNEG for a large negative number.
argument: ``--BackgroundFillValue %s``
interpolationMode: ('NearestNeighbor' or 'Linear' or
'ResampleInPlace' or 'BSpline' or 'WindowedSinc' or 'Hamming' or
'Cosine' or 'Welch' or 'Lanczos' or 'Blackman')
Type of interpolation to be used when applying transform to moving
volume. Options are Linear, ResampleInPlace, NearestNeighbor,
BSpline, or WindowedSinc
argument: ``--interpolationMode %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:
OutputresampleMSP: (a pathlike object or string representing an
existing file)
, The image to be output.,
resultsDir: (a pathlike object or string representing an existing
directory)
, The directory for the results to be written.,
BRAINSClipInferior¶
Wraps the executable command `` BRAINSClipInferior ``.
title: Clip Inferior of Center of Brain (BRAINS)
category: Utilities.BRAINS
description: This program will read the inputVolume as a short int image, write the BackgroundFillValue everywhere inferior to the lower bound, and write the resulting clipped short int image in the outputVolume.
version: 1.0
Inputs:
[Optional]
inputVolume: (a pathlike object or string representing an existing
file)
Input image to make a clipped short int copy from.
argument: ``--inputVolume %s``
outputVolume: (a boolean or a pathlike object or string representing
a file)
Output image, a short int copy of the upper portion of the input
image, filled with BackgroundFillValue.
argument: ``--outputVolume %s``
acLowerBound: (a float)
, When the input image to the output image, replace the image with
the BackgroundFillValue everywhere below the plane This Far in
physical units (millimeters) below (inferior to) the AC point
(assumed to be the voxel field middle.) The oversize default was
chosen to have no effect. Based on visualizing a thousand masks in
the IPIG study, we recommend a limit no smaller than 80.0 mm.,
argument: ``--acLowerBound %f``
BackgroundFillValue: (a unicode string)
Fill the background of image with specified short int value. Enter
number or use BIGNEG for a large negative number.
argument: ``--BackgroundFillValue %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:
outputVolume: (a pathlike object or string representing an existing
file)
Output image, a short int copy of the upper portion of the input
image, filled with BackgroundFillValue.
BRAINSConstellationModeler¶
Wraps the executable command `` BRAINSConstellationModeler ``.
title: Generate Landmarks Model (BRAINS)
category: Utilities.BRAINS
description: Train up a model for BRAINSConstellationDetector
Inputs:
[Optional]
verbose: (a boolean)
, Show more verbose output,
argument: ``--verbose ``
inputTrainingList: (a pathlike object or string representing an
existing file)
, Setup file, giving all parameters for training up a template model
for each landmark.,
argument: ``--inputTrainingList %s``
outputModel: (a boolean or a pathlike object or string representing a
file)
, The full filename of the output model file.,
argument: ``--outputModel %s``
saveOptimizedLandmarks: (a boolean)
, Flag to make a new subject-specific landmark definition file in
the same format produced by Slicer3 with the optimized landmark (the
detected RP, AC, and PC) in it. Useful to tighten the variances in
the ConstellationModeler.,
argument: ``--saveOptimizedLandmarks ``
optimizedLandmarksFilenameExtender: (a unicode string)
, If the trainingList is (indexFullPathName) and contains landmark
data filenames [path]/[filename].fcsv , make the optimized landmarks
filenames out of [path]/[filename](thisExtender) and the optimized
version of the input trainingList out of
(indexFullPathName)(thisExtender) , when you rewrite all the
landmarks according to the saveOptimizedLandmarks flag.,
argument: ``--optimizedLandmarksFilenameExtender %s``
resultsDir: (a boolean or a pathlike object or string representing a
directory)
, The directory for the results to be written.,
argument: ``--resultsDir %s``
mspQualityLevel: (an integer (int or long))
, Flag cotrols how agressive the MSP is estimated. 0=quick estimate
(9 seconds), 1=normal estimate (11 seconds), 2=great estimate (22
seconds), 3=best estimate (58 seconds).,
argument: ``--mspQualityLevel %d``
rescaleIntensities: (a boolean)
, Flag to turn on rescaling image intensities on input.,
argument: ``--rescaleIntensities ``
trimRescaledIntensities: (a float)
, Turn on clipping the rescaled image one-tailed on input. Units of
standard deviations above the mean. Very large values are very
permissive. Non-positive value turns clipping off. Defaults to
removing 0.00001 of a normal tail above the mean.,
argument: ``--trimRescaledIntensities %f``
rescaleIntensitiesOutputRange: (a list of items which are an integer
(int or long))
, This pair of integers gives the lower and upper bounds on the
signal portion of the output image. Out-of-field voxels are taken
from BackgroundFillValue.,
argument: ``--rescaleIntensitiesOutputRange %s``
BackgroundFillValue: (a unicode string)
Fill the background of image with specified short int value. Enter
number or use BIGNEG for a large negative number.
argument: ``--BackgroundFillValue %s``
writedebuggingImagesLevel: (an integer (int or long))
, This flag controls if debugging images are produced. By default
value of 0 is no images. Anything greater than zero will be
increasing level of debugging images.,
argument: ``--writedebuggingImagesLevel %d``
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:
outputModel: (a pathlike object or string representing an existing
file)
, The full filename of the output model file.,
resultsDir: (a pathlike object or string representing an existing
directory)
, The directory for the results to be written.,
BRAINSEyeDetector¶
Wraps the executable command `` BRAINSEyeDetector ``.
title: Eye Detector (BRAINS)
category: Utilities.BRAINS
version: 1.0
documentation-url: http://www.nitrc.org/projects/brainscdetector/
Inputs:
[Optional]
numberOfThreads: (an integer (int or long))
Explicitly specify the maximum number of threads to use.
argument: ``--numberOfThreads %d``
inputVolume: (a pathlike object or string representing an existing
file)
The input volume
argument: ``--inputVolume %s``
outputVolume: (a boolean or a pathlike object or string representing
a file)
The output volume
argument: ``--outputVolume %s``
debugDir: (a unicode string)
A place for debug information
argument: ``--debugDir %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: (a pathlike object or string representing an existing
file)
The output volume
BRAINSInitializedControlPoints¶
Wraps the executable command `` BRAINSInitializedControlPoints ``.
title: Initialized Control Points (BRAINS)
category: Utilities.BRAINS
description: Outputs bspline control points as landmarks
version: 0.1.0.$Revision: 916 $(alpha)
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: Mark Scully
acknowledgements: This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Additional support for Mark Scully and Hans Johnson at the University of Iowa.
Inputs:
[Optional]
inputVolume: (a pathlike object or string representing an existing
file)
Input Volume
argument: ``--inputVolume %s``
outputVolume: (a boolean or a pathlike object or string representing
a file)
Output Volume
argument: ``--outputVolume %s``
splineGridSize: (a list of items which are an integer (int or long))
The number of subdivisions of the BSpline Grid to be centered on the
image space. Each dimension must have at least 3 subdivisions for
the BSpline to be correctly computed.
argument: ``--splineGridSize %s``
permuteOrder: (a list of items which are an integer (int or long))
The permutation order for the images. The default is 0,1,2 (i.e. no
permutation)
argument: ``--permuteOrder %s``
outputLandmarksFile: (a unicode string)
Output filename
argument: ``--outputLandmarksFile %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:
outputVolume: (a pathlike object or string representing an existing
file)
Output Volume
BRAINSLandmarkInitializer¶
Wraps the executable command `` BRAINSLandmarkInitializer ``.
title: BRAINSLandmarkInitializer
category: Utilities.BRAINS
description: Create transformation file (*mat) from a pair of landmarks (*fcsv) files.
version: 1.0
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: Eunyoung Regina Kim
Inputs:
[Optional]
inputFixedLandmarkFilename: (a pathlike object or string representing
an existing file)
input fixed landmark. *.fcsv
argument: ``--inputFixedLandmarkFilename %s``
inputMovingLandmarkFilename: (a pathlike object or string
representing an existing file)
input moving landmark. *.fcsv
argument: ``--inputMovingLandmarkFilename %s``
inputWeightFilename: (a pathlike object or string representing an
existing file)
Input weight file name for landmarks. Higher weighted landmark will
be considered more heavily. Weights are propotional, that is the
magnitude of weights will be normalized by its minimum and maximum
value.
argument: ``--inputWeightFilename %s``
outputTransformFilename: (a boolean or a pathlike object or string
representing a file)
output transform file name (ex: ./outputTransform.mat)
argument: ``--outputTransformFilename %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:
outputTransformFilename: (a pathlike object or string representing an
existing file)
output transform file name (ex: ./outputTransform.mat)
BRAINSLinearModelerEPCA¶
Wraps the executable command `` BRAINSLinearModelerEPCA ``.
title: Landmark Linear Modeler (BRAINS)
category: Utilities.BRAINS
description: Training linear model using EPCA. Implementation based on my MS thesis, “A METHOD FOR AUTOMATED LANDMARK CONSTELLATION DETECTION USING EVOLUTIONARY PRINCIPAL COMPONENTS AND STATISTICAL SHAPE MODELS”
version: 1.0
documentation-url: http://www.nitrc.org/projects/brainscdetector/
Inputs:
[Optional]
inputTrainingList: (a pathlike object or string representing an
existing file)
Input Training Landmark List Filename,
argument: ``--inputTrainingList %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:
None
BRAINSLmkTransform¶
Wraps the executable command `` BRAINSLmkTransform ``.
title: Landmark Transform (BRAINS)
category: Utilities.BRAINS
description: This utility program estimates the affine transform to align the fixed landmarks to the moving landmarks, and then generate the resampled moving image to the same physical space as that of the reference image.
version: 1.0
documentation-url: http://www.nitrc.org/projects/brainscdetector/
Inputs:
[Optional]
inputMovingLandmarks: (a pathlike object or string representing an
existing file)
Input Moving Landmark list file in fcsv,
argument: ``--inputMovingLandmarks %s``
inputFixedLandmarks: (a pathlike object or string representing an
existing file)
Input Fixed Landmark list file in fcsv,
argument: ``--inputFixedLandmarks %s``
outputAffineTransform: (a boolean or a pathlike object or string
representing a file)
The filename for the estimated affine transform,
argument: ``--outputAffineTransform %s``
inputMovingVolume: (a pathlike object or string representing an
existing file)
The filename of input moving volume
argument: ``--inputMovingVolume %s``
inputReferenceVolume: (a pathlike object or string representing an
existing file)
The filename of the reference volume
argument: ``--inputReferenceVolume %s``
outputResampledVolume: (a boolean or a pathlike object or string
representing a file)
The filename of the output resampled volume
argument: ``--outputResampledVolume %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:
outputAffineTransform: (a pathlike object or string representing an
existing file)
The filename for the estimated affine transform,
outputResampledVolume: (a pathlike object or string representing an
existing file)
The filename of the output resampled volume
BRAINSMush¶
Wraps the executable command `` BRAINSMush ``.
title: Brain Extraction from T1/T2 image (BRAINS)
category: Utilities.BRAINS
description: This program: 1) generates a weighted mixture image optimizing the mean and variance and 2) produces a mask of the brain volume
version: 0.1.0.$Revision: 1.4 $(alpha)
documentation-url: http:://mri.radiology.uiowa.edu
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: This tool is a modification by Steven Dunn of a program developed by Greg Harris and Ron Pierson.
acknowledgements: This work was developed by the University of Iowa Departments of Radiology and Psychiatry. This software was supported in part of NIH/NINDS award NS050568.
Inputs:
[Optional]
inputFirstVolume: (a pathlike object or string representing an
existing file)
Input image (1) for mixture optimization
argument: ``--inputFirstVolume %s``
inputSecondVolume: (a pathlike object or string representing an
existing file)
Input image (2) for mixture optimization
argument: ``--inputSecondVolume %s``
inputMaskVolume: (a pathlike object or string representing an
existing file)
Input label image for mixture optimization
argument: ``--inputMaskVolume %s``
outputWeightsFile: (a boolean or a pathlike object or string
representing a file)
Output Weights File
argument: ``--outputWeightsFile %s``
outputVolume: (a boolean or a pathlike object or string representing
a file)
The MUSH image produced from the T1 and T2 weighted images
argument: ``--outputVolume %s``
outputMask: (a boolean or a pathlike object or string representing a
file)
The brain volume mask generated from the MUSH image
argument: ``--outputMask %s``
seed: (a list of items which are an integer (int or long))
Seed Point for Brain Region Filling
argument: ``--seed %s``
desiredMean: (a float)
Desired mean within the mask for weighted sum of both images.
argument: ``--desiredMean %f``
desiredVariance: (a float)
Desired variance within the mask for weighted sum of both images.
argument: ``--desiredVariance %f``
lowerThresholdFactorPre: (a float)
Lower threshold factor for finding an initial brain mask
argument: ``--lowerThresholdFactorPre %f``
upperThresholdFactorPre: (a float)
Upper threshold factor for finding an initial brain mask
argument: ``--upperThresholdFactorPre %f``
lowerThresholdFactor: (a float)
Lower threshold factor for defining the brain mask
argument: ``--lowerThresholdFactor %f``
upperThresholdFactor: (a float)
Upper threshold factor for defining the brain mask
argument: ``--upperThresholdFactor %f``
boundingBoxSize: (a list of items which are an integer (int or long))
Size of the cubic bounding box mask used when no brain mask is
present
argument: ``--boundingBoxSize %s``
boundingBoxStart: (a list of items which are an integer (int or
long))
XYZ point-coordinate for the start of the cubic bounding box mask
used when no brain mask is present
argument: ``--boundingBoxStart %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:
outputWeightsFile: (a pathlike object or string representing an
existing file)
Output Weights File
outputVolume: (a pathlike object or string representing an existing
file)
The MUSH image produced from the T1 and T2 weighted images
outputMask: (a pathlike object or string representing an existing
file)
The brain volume mask generated from the MUSH image
BRAINSSnapShotWriter¶
Wraps the executable command `` BRAINSSnapShotWriter ``.
title: BRAINSSnapShotWriter
category: Utilities.BRAINS
description: Create 2D snapshot of input images. Mask images are color-coded
version: 1.0
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: Eunyoung Regina Kim
Inputs:
[Optional]
inputVolumes: (a list of items which are a pathlike object or string
representing an existing file)
Input image volume list to be extracted as 2D image. Multiple input
is possible. At least one input is required.
argument: ``--inputVolumes %s...``
inputBinaryVolumes: (a list of items which are a pathlike object or
string representing an existing file)
Input mask (binary) volume list to be extracted as 2D image.
Multiple input is possible.
argument: ``--inputBinaryVolumes %s...``
inputSliceToExtractInPhysicalPoint: (a list of items which are a
float)
2D slice number of input images. For autoWorkUp output, which AC-PC
aligned, 0,0,0 will be the center.
argument: ``--inputSliceToExtractInPhysicalPoint %s``
inputSliceToExtractInIndex: (a list of items which are an integer
(int or long))
2D slice number of input images. For size of 256*256*256 image, 128
is usually used.
argument: ``--inputSliceToExtractInIndex %s``
inputSliceToExtractInPercent: (a list of items which are an integer
(int or long))
2D slice number of input images. Percentage input from 0%-100%. (ex.
--inputSliceToExtractInPercent 50,50,50
argument: ``--inputSliceToExtractInPercent %s``
inputPlaneDirection: (a list of items which are an integer (int or
long))
Plane to display. In general, 0=saggital, 1=coronal, and 2=axial
plane.
argument: ``--inputPlaneDirection %s``
outputFilename: (a boolean or a pathlike object or string
representing a file)
2D file name of input images. Required.
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: (a pathlike object or string representing an existing
file)
2D file name of input images. Required.
BRAINSTransformConvert¶
Wraps the executable command `` BRAINSTransformConvert ``.
title: BRAINS Transform Convert
category: Utilities.BRAINS
description: Convert ITK transforms to higher order transforms
version: 1.0
documentation-url: A utility to convert between transform file formats.
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: Hans J. Johnson,Kent Williams, Ali Ghayoor
Inputs:
[Optional]
inputTransform: (a pathlike object or string representing an existing
file)
argument: ``--inputTransform %s``
referenceVolume: (a pathlike object or string representing an
existing file)
argument: ``--referenceVolume %s``
outputTransformType: ('Affine' or 'VersorRigid' or 'ScaleVersor' or
'ScaleSkewVersor' or 'DisplacementField' or 'Same')
The target transformation type. Must be conversion-compatible with
the input transform type
argument: ``--outputTransformType %s``
outputPrecisionType: ('double' or 'float')
Precision type of the output transform. It can be either single
precision or double precision
argument: ``--outputPrecisionType %s``
displacementVolume: (a boolean or a pathlike object or string
representing a file)
argument: ``--displacementVolume %s``
outputTransform: (a boolean or a pathlike object or string
representing a file)
argument: ``--outputTransform %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:
displacementVolume: (a pathlike object or string representing an
existing file)
outputTransform: (a pathlike object or string representing an
existing file)
BRAINSTrimForegroundInDirection¶
Wraps the executable command `` BRAINSTrimForegroundInDirection ``.
title: Trim Foreground In Direction (BRAINS)
category: Utilities.BRAINS
description: This program will trim off the neck and also air-filling noise from the inputImage.
version: 0.1
documentation-url: http://www.nitrc.org/projects/art/
Inputs:
[Optional]
inputVolume: (a pathlike object or string representing an existing
file)
Input image to trim off the neck (and also air-filling noise.)
argument: ``--inputVolume %s``
outputVolume: (a boolean or a pathlike object or string representing
a file)
Output image with neck and air-filling noise trimmed isotropic image
with AC at center of image.
argument: ``--outputVolume %s``
directionCode: (an integer (int or long))
, This flag chooses which dimension to compare. The sign lets you
flip direction.,
argument: ``--directionCode %d``
otsuPercentileThreshold: (a float)
, This is a parameter to FindLargestForegroundFilledMask, which is
employed to trim off air-filling noise.,
argument: ``--otsuPercentileThreshold %f``
closingSize: (an integer (int or long))
, This is a parameter to FindLargestForegroundFilledMask,
argument: ``--closingSize %d``
headSizeLimit: (a float)
, Use this to vary from the command line our search for how much
upper tissue is head for the center-of-mass calculation. Units are
CCs, not cubic millimeters.,
argument: ``--headSizeLimit %f``
BackgroundFillValue: (a unicode string)
Fill the background of image with specified short int value. Enter
number or use BIGNEG for a large negative number.
argument: ``--BackgroundFillValue %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:
outputVolume: (a pathlike object or string representing an existing
file)
Output image with neck and air-filling noise trimmed isotropic image
with AC at center of image.
CleanUpOverlapLabels¶
Wraps the executable command `` CleanUpOverlapLabels ``.
title: Clean Up Overla Labels
category: Utilities.BRAINS
description: Take a series of input binary images and clean up for those overlapped area. Binary volumes given first always wins out
version: 0.1.0
contributor: Eun Young Kim
Inputs:
[Optional]
inputBinaryVolumes: (a list of items which are a pathlike object or
string representing an existing file)
The list of binary images to be checked and cleaned up. Order is
important. Binary volume given first always wins out.
argument: ``--inputBinaryVolumes %s...``
outputBinaryVolumes: (a boolean or a list of items which are a
pathlike object or string representing a file)
The output label map images, with integer values in it. Each label
value specified in the inputLabels is combined into this output
label map volume
argument: ``--outputBinaryVolumes %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:
outputBinaryVolumes: (a list of items which are a pathlike object or
string representing an existing file)
The output label map images, with integer values in it. Each label
value specified in the inputLabels is combined into this output
label map volume
FindCenterOfBrain¶
Wraps the executable command `` FindCenterOfBrain ``.
title: Center Of Brain (BRAINS)
category: Utilities.BRAINS
description: Finds the center point of a brain
version: 3.0.0
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: Hans J. Johnson, hans-johnson -at- uiowa.edu, http://wwww.psychiatry.uiowa.edu
acknowledgements: Hans Johnson(1,3,4); Kent Williams(1); (1=University of Iowa Department of Psychiatry, 3=University of Iowa Department of Biomedical Engineering, 4=University of Iowa Department of Electrical and Computer Engineering
Inputs:
[Optional]
inputVolume: (a pathlike object or string representing an existing
file)
The image in which to find the center.
argument: ``--inputVolume %s``
imageMask: (a pathlike object or string representing an existing
file)
argument: ``--imageMask %s``
clippedImageMask: (a boolean or a pathlike object or string
representing a file)
argument: ``--clippedImageMask %s``
maximize: (a boolean)
argument: ``--maximize ``
axis: (an integer (int or long))
argument: ``--axis %d``
otsuPercentileThreshold: (a float)
argument: ``--otsuPercentileThreshold %f``
closingSize: (an integer (int or long))
argument: ``--closingSize %d``
headSizeLimit: (a float)
argument: ``--headSizeLimit %f``
headSizeEstimate: (a float)
argument: ``--headSizeEstimate %f``
backgroundValue: (an integer (int or long))
argument: ``--backgroundValue %d``
generateDebugImages: (a boolean)
argument: ``--generateDebugImages ``
debugDistanceImage: (a boolean or a pathlike object or string
representing a file)
argument: ``--debugDistanceImage %s``
debugGridImage: (a boolean or a pathlike object or string
representing a file)
argument: ``--debugGridImage %s``
debugAfterGridComputationsForegroundImage: (a boolean or a pathlike
object or string representing a file)
argument: ``--debugAfterGridComputationsForegroundImage %s``
debugClippedImageMask: (a boolean or a pathlike object or string
representing a file)
argument: ``--debugClippedImageMask %s``
debugTrimmedImage: (a boolean or a pathlike object or string
representing a file)
argument: ``--debugTrimmedImage %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:
clippedImageMask: (a pathlike object or string representing an
existing file)
debugDistanceImage: (a pathlike object or string representing an
existing file)
debugGridImage: (a pathlike object or string representing an existing
file)
debugAfterGridComputationsForegroundImage: (a pathlike object or
string representing an existing file)
debugClippedImageMask: (a pathlike object or string representing an
existing file)
debugTrimmedImage: (a pathlike object or string representing an
existing file)
GenerateLabelMapFromProbabilityMap¶
Wraps the executable command `` GenerateLabelMapFromProbabilityMap ``.
title: Label Map from Probability Images
category: Utilities.BRAINS
description: Given a list of probability maps for labels, create a discrete label map where only the highest probability region is used for the labeling.
version: 0.1
contributor: University of Iowa Department of Psychiatry, http:://www.psychiatry.uiowa.edu
Inputs:
[Optional]
inputVolumes: (a list of items which are a pathlike object or string
representing an existing file)
The Input probaiblity images to be computed for lable maps
argument: ``--inputVolumes %s...``
outputLabelVolume: (a boolean or a pathlike object or string
representing a file)
The Input binary image for region of interest
argument: ``--outputLabelVolume %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:
outputLabelVolume: (a pathlike object or string representing an
existing file)
The Input binary image for region of interest
ImageRegionPlotter¶
Wraps the executable command `` ImageRegionPlotter ``.
title: Write Out Image Intensities
category: Utilities.BRAINS
description: For Analysis
version: 0.1
contributor: University of Iowa Department of Psychiatry, http:://www.psychiatry.uiowa.edu
Inputs:
[Optional]
inputVolume1: (a pathlike object or string representing an existing
file)
The Input image to be computed for statistics
argument: ``--inputVolume1 %s``
inputVolume2: (a pathlike object or string representing an existing
file)
The Input image to be computed for statistics
argument: ``--inputVolume2 %s``
inputBinaryROIVolume: (a pathlike object or string representing an
existing file)
The Input binary image for region of interest
argument: ``--inputBinaryROIVolume %s``
inputLabelVolume: (a pathlike object or string representing an
existing file)
The Label Image
argument: ``--inputLabelVolume %s``
numberOfHistogramBins: (an integer (int or long))
the number of histogram levels
argument: ``--numberOfHistogramBins %d``
outputJointHistogramData: (a unicode string)
output data file name
argument: ``--outputJointHistogramData %s``
useROIAUTO: (a boolean)
Use ROIAUTO to compute region of interest. This cannot be used with
inputLabelVolume
argument: ``--useROIAUTO ``
useIntensityForHistogram: (a boolean)
Create Intensity Joint Histogram instead of Quantile Joint
Histogram
argument: ``--useIntensityForHistogram ``
verbose: (a boolean)
print debugging information,
argument: ``--verbose ``
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
JointHistogram¶
Wraps the executable command `` JointHistogram ``.
title: Write Out Image Intensities
category: Utilities.BRAINS
description: For Analysis
version: 0.1
contributor: University of Iowa Department of Psychiatry, http:://www.psychiatry.uiowa.edu
Inputs:
[Optional]
inputVolumeInXAxis: (a pathlike object or string representing an
existing file)
The Input image to be computed for statistics
argument: ``--inputVolumeInXAxis %s``
inputVolumeInYAxis: (a pathlike object or string representing an
existing file)
The Input image to be computed for statistics
argument: ``--inputVolumeInYAxis %s``
inputMaskVolumeInXAxis: (a pathlike object or string representing an
existing file)
Input mask volume for inputVolumeInXAxis. Histogram will be computed
just for the masked region
argument: ``--inputMaskVolumeInXAxis %s``
inputMaskVolumeInYAxis: (a pathlike object or string representing an
existing file)
Input mask volume for inputVolumeInYAxis. Histogram will be computed
just for the masked region
argument: ``--inputMaskVolumeInYAxis %s``
outputJointHistogramImage: (a unicode string)
output joint histogram image file name. Histogram is usually 2D
image.
argument: ``--outputJointHistogramImage %s``
verbose: (a boolean)
print debugging information,
argument: ``--verbose ``
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
ShuffleVectorsModule¶
Wraps the executable command `` ShuffleVectorsModule ``.
title: ShuffleVectors
category: Utilities.BRAINS
description: Automatic Segmentation using neural networks
version: 1.0
license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
contributor: Hans Johnson
Inputs:
[Optional]
inputVectorFileBaseName: (a pathlike object or string representing an
existing file)
input vector file name prefix. Usually end with .txt and header file
has prost fix of .txt.hdr
argument: ``--inputVectorFileBaseName %s``
outputVectorFileBaseName: (a boolean or a pathlike object or string
representing a file)
output vector file name prefix. Usually end with .txt and header
file has prost fix of .txt.hdr
argument: ``--outputVectorFileBaseName %s``
resampleProportion: (a float)
downsample size of 1 will be the same size as the input images,
downsample size of 3 will throw 2/3 the vectors away.
argument: ``--resampleProportion %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:
outputVectorFileBaseName: (a pathlike object or string representing
an existing file)
output vector file name prefix. Usually end with .txt and header
file has prost fix of .txt.hdr
fcsv_to_hdf5¶
Wraps the executable command `` fcsv_to_hdf5 ``.
title: fcsv_to_hdf5 (BRAINS)
category: Utilities.BRAINS
description: Convert a collection of fcsv files to a HDF5 format file
Inputs:
[Optional]
versionID: (a unicode string)
, Current version ID. It should be match with the version of BCD
that will be using the output model file,
argument: ``--versionID %s``
landmarksInformationFile: (a boolean or a pathlike object or string
representing a file)
, name of HDF5 file to write matrices into,
argument: ``--landmarksInformationFile %s``
landmarkTypesList: (a pathlike object or string representing an
existing file)
, file containing list of landmark types,
argument: ``--landmarkTypesList %s``
modelFile: (a boolean or a pathlike object or string representing a
file)
, name of HDF5 file containing BRAINSConstellationDetector Model
file (LLSMatrices, LLSMeans and LLSSearchRadii),
argument: ``--modelFile %s``
landmarkGlobPattern: (a unicode string)
Glob pattern to select fcsv files
argument: ``--landmarkGlobPattern %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:
landmarksInformationFile: (a pathlike object or string representing
an existing file)
, name of HDF5 file to write matrices into,
modelFile: (a pathlike object or string representing an existing
file)
, name of HDF5 file containing BRAINSConstellationDetector Model
file (LLSMatrices, LLSMeans and LLSSearchRadii),
insertMidACPCpoint¶
Wraps the executable command `` insertMidACPCpoint ``.
title: MidACPC Landmark Insertion
category: Utilities.BRAINS
description: This program gets a landmark fcsv file and adds a new landmark as the midpoint between AC and PC points to the output landmark fcsv file
contributor: Ali Ghayoor
Inputs:
[Optional]
inputLandmarkFile: (a pathlike object or string representing an
existing file)
Input landmark file (.fcsv)
argument: ``--inputLandmarkFile %s``
outputLandmarkFile: (a boolean or a pathlike object or string
representing a file)
Output landmark file (.fcsv)
argument: ``--outputLandmarkFile %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:
outputLandmarkFile: (a pathlike object or string representing an
existing file)
Output landmark file (.fcsv)
landmarksConstellationAligner¶
Wraps the executable command `` landmarksConstellationAligner ``.
title: MidACPC Landmark Insertion
category: Utilities.BRAINS
description: This program converts the original landmark files to the acpc-aligned landmark files
contributor: Ali Ghayoor
Inputs:
[Optional]
inputLandmarksPaired: (a pathlike object or string representing an
existing file)
Input landmark file (.fcsv)
argument: ``--inputLandmarksPaired %s``
outputLandmarksPaired: (a boolean or a pathlike object or string
representing a file)
Output landmark file (.fcsv)
argument: ``--outputLandmarksPaired %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:
outputLandmarksPaired: (a pathlike object or string representing an
existing file)
Output landmark file (.fcsv)
landmarksConstellationWeights¶
Wraps the executable command `` landmarksConstellationWeights ``.
title: Generate Landmarks Weights (BRAINS)
category: Utilities.BRAINS
description: Train up a list of Weights for the Landmarks in BRAINSConstellationDetector
Inputs:
[Optional]
inputTrainingList: (a pathlike object or string representing an
existing file)
, Setup file, giving all parameters for training up a Weight list
for landmark.,
argument: ``--inputTrainingList %s``
inputTemplateModel: (a pathlike object or string representing an
existing file)
User-specified template model.,
argument: ``--inputTemplateModel %s``
LLSModel: (a pathlike object or string representing an existing file)
Linear least squares model filename in HD5 format
argument: ``--LLSModel %s``
outputWeightsList: (a boolean or a pathlike object or string
representing a file)
, The filename of a csv file which is a list of landmarks and their
corresponding weights.,
argument: ``--outputWeightsList %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:
outputWeightsList: (a pathlike object or string representing an
existing file)
, The filename of a csv file which is a list of landmarks and their
corresponding weights.,