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# interfaces.semtools.utilities.brains

## BRAINSAlignMSP

Link to code

Wraps command ** BRAINSAlignMSP **

title: Align Mid Saggital Brain (BRAINS)

category: Utilities.BRAINS

description: Resample an image into ACPC alignement ACPCDetect

Inputs:

    [Mandatory]

    [Optional]
    BackgroundFillValue: (a unicode string)
            Fill the background of image with specified short int value. Enter
            number or use BIGNEG for a large negative number.
            flag: --BackgroundFillValue %s
    OutputresampleMSP: (a boolean or a file name)
            , The image to be output.,
            flag: --OutputresampleMSP %s
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputVolume: (an existing file name)
            , The Image to be resampled,
            flag: --inputVolume %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
            flag: --interpolationMode %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).,
            flag: --mspQualityLevel %d
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    rescaleIntensities: (a boolean)
            , Flag to turn on rescaling image intensities on input.,
            flag: --rescaleIntensities
    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.,
            flag: --rescaleIntensitiesOutputRange %s
    resultsDir: (a boolean or a directory name)
            , The directory for the results to be written.,
            flag: --resultsDir %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    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.,
            flag: --trimRescaledIntensities %f
    verbose: (a boolean)
            , Show more verbose output,
            flag: --verbose
    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.,
            flag: --writedebuggingImagesLevel %d

Outputs:

    OutputresampleMSP: (an existing file name)
            , The image to be output.,
    resultsDir: (an existing directory name)
            , The directory for the results to be written.,

## BRAINSClipInferior

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    BackgroundFillValue: (a unicode string)
            Fill the background of image with specified short int value. Enter
            number or use BIGNEG for a large negative number.
            flag: --BackgroundFillValue %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.,
            flag: --acLowerBound %f
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputVolume: (an existing file name)
            Input image to make a clipped short int copy from.
            flag: --inputVolume %s
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    outputVolume: (a boolean or a file name)
            Output image, a short int copy of the upper portion of the input
            image, filled with BackgroundFillValue.
            flag: --outputVolume %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputVolume: (an existing file name)
            Output image, a short int copy of the upper portion of the input
            image, filled with BackgroundFillValue.

## BRAINSConstellationModeler

Link to code

Wraps command ** BRAINSConstellationModeler **

title: Generate Landmarks Model (BRAINS)

category: Utilities.BRAINS

description: Train up a model for BRAINSConstellationDetector

Inputs:

    [Mandatory]

    [Optional]
    BackgroundFillValue: (a unicode string)
            Fill the background of image with specified short int value. Enter
            number or use BIGNEG for a large negative number.
            flag: --BackgroundFillValue %s
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputTrainingList: (an existing file name)
            , Setup file, giving all parameters for training up a template model
            for each landmark.,
            flag: --inputTrainingList %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).,
            flag: --mspQualityLevel %d
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    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.,
            flag: --optimizedLandmarksFilenameExtender %s
    outputModel: (a boolean or a file name)
            , The full filename of the output model file.,
            flag: --outputModel %s
    rescaleIntensities: (a boolean)
            , Flag to turn on rescaling image intensities on input.,
            flag: --rescaleIntensities
    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.,
            flag: --rescaleIntensitiesOutputRange %s
    resultsDir: (a boolean or a directory name)
            , The directory for the results to be written.,
            flag: --resultsDir %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.,
            flag: --saveOptimizedLandmarks
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    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.,
            flag: --trimRescaledIntensities %f
    verbose: (a boolean)
            , Show more verbose output,
            flag: --verbose
    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.,
            flag: --writedebuggingImagesLevel %d

Outputs:

    outputModel: (an existing file name)
            , The full filename of the output model file.,
    resultsDir: (an existing directory name)
            , The directory for the results to be written.,

## BRAINSEyeDetector

Link to code

Wraps command ** BRAINSEyeDetector **

title: Eye Detector (BRAINS)

category: Utilities.BRAINS

version: 1.0

documentation-url: http://www.nitrc.org/projects/brainscdetector/

Inputs:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    debugDir: (a unicode string)
            A place for debug information
            flag: --debugDir %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputVolume: (an existing file name)
            The input volume
            flag: --inputVolume %s
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    outputVolume: (a boolean or a file name)
            The output volume
            flag: --outputVolume %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputVolume: (an existing file name)
            The output volume

## BRAINSInitializedControlPoints

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputVolume: (an existing file name)
            Input Volume
            flag: --inputVolume %s
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    outputLandmarksFile: (a unicode string)
            Output filename
            flag: --outputLandmarksFile %s
    outputVolume: (a boolean or a file name)
            Output Volume
            flag: --outputVolume %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)
            flag: --permuteOrder %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.
            flag: --splineGridSize %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputVolume: (an existing file name)
            Output Volume

## BRAINSLandmarkInitializer

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputFixedLandmarkFilename: (an existing file name)
            input fixed landmark. *.fcsv
            flag: --inputFixedLandmarkFilename %s
    inputMovingLandmarkFilename: (an existing file name)
            input moving landmark. *.fcsv
            flag: --inputMovingLandmarkFilename %s
    inputWeightFilename: (an existing file name)
            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.
            flag: --inputWeightFilename %s
    outputTransformFilename: (a boolean or a file name)
            output transform file name (ex: ./outputTransform.mat)
            flag: --outputTransformFilename %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputTransformFilename: (an existing file name)
            output transform file name (ex: ./outputTransform.mat)

## BRAINSLinearModelerEPCA

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputTrainingList: (an existing file name)
            Input Training Landmark List Filename,
            flag: --inputTrainingList %s
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    None

## BRAINSLmkTransform

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputFixedLandmarks: (an existing file name)
            Input Fixed Landmark list file in fcsv,
            flag: --inputFixedLandmarks %s
    inputMovingLandmarks: (an existing file name)
            Input Moving Landmark list file in fcsv,
            flag: --inputMovingLandmarks %s
    inputMovingVolume: (an existing file name)
            The filename of input moving volume
            flag: --inputMovingVolume %s
    inputReferenceVolume: (an existing file name)
            The filename of the reference volume
            flag: --inputReferenceVolume %s
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    outputAffineTransform: (a boolean or a file name)
            The filename for the estimated affine transform,
            flag: --outputAffineTransform %s
    outputResampledVolume: (a boolean or a file name)
            The filename of the output resampled volume
            flag: --outputResampledVolume %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputAffineTransform: (an existing file name)
            The filename for the estimated affine transform,
    outputResampledVolume: (an existing file name)
            The filename of the output resampled volume

## BRAINSMush

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    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
            flag: --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
            flag: --boundingBoxStart %s
    desiredMean: (a float)
            Desired mean within the mask for weighted sum of both images.
            flag: --desiredMean %f
    desiredVariance: (a float)
            Desired variance within the mask for weighted sum of both images.
            flag: --desiredVariance %f
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputFirstVolume: (an existing file name)
            Input image (1) for mixture optimization
            flag: --inputFirstVolume %s
    inputMaskVolume: (an existing file name)
            Input label image for mixture optimization
            flag: --inputMaskVolume %s
    inputSecondVolume: (an existing file name)
            Input image (2) for mixture optimization
            flag: --inputSecondVolume %s
    lowerThresholdFactor: (a float)
            Lower threshold factor for defining the brain mask
            flag: --lowerThresholdFactor %f
    lowerThresholdFactorPre: (a float)
            Lower threshold factor for finding an initial brain mask
            flag: --lowerThresholdFactorPre %f
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    outputMask: (a boolean or a file name)
            The brain volume mask generated from the MUSH image
            flag: --outputMask %s
    outputVolume: (a boolean or a file name)
            The MUSH image produced from the T1 and T2 weighted images
            flag: --outputVolume %s
    outputWeightsFile: (a boolean or a file name)
            Output Weights File
            flag: --outputWeightsFile %s
    seed: (a list of items which are an integer (int or long))
            Seed Point for Brain Region Filling
            flag: --seed %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    upperThresholdFactor: (a float)
            Upper threshold factor for defining the brain mask
            flag: --upperThresholdFactor %f
    upperThresholdFactorPre: (a float)
            Upper threshold factor for finding an initial brain mask
            flag: --upperThresholdFactorPre %f

Outputs:

    outputMask: (an existing file name)
            The brain volume mask generated from the MUSH image
    outputVolume: (an existing file name)
            The MUSH image produced from the T1 and T2 weighted images
    outputWeightsFile: (an existing file name)
            Output Weights File

## BRAINSSnapShotWriter

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputBinaryVolumes: (a list of items which are an existing file name)
            Input mask (binary) volume list to be extracted as 2D image.
            Multiple input is possible.
            flag: --inputBinaryVolumes %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.
            flag: --inputPlaneDirection %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.
            flag: --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
            flag: --inputSliceToExtractInPercent %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.
            flag: --inputSliceToExtractInPhysicalPoint %s
    inputVolumes: (a list of items which are an existing file name)
            Input image volume list to be extracted as 2D image. Multiple input
            is possible. At least one input is required.
            flag: --inputVolumes %s...
    outputFilename: (a boolean or a file name)
            2D file name of input images. Required.
            flag: --outputFilename %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputFilename: (an existing file name)
            2D file name of input images. Required.

## BRAINSTransformConvert

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    displacementVolume: (a boolean or a file name)
            flag: --displacementVolume %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputTransform: (an existing file name)
            flag: --inputTransform %s
    outputPrecisionType: ('double' or 'float')
            Precision type of the output transform. It can be either single
            precision or double precision
            flag: --outputPrecisionType %s
    outputTransform: (a boolean or a file name)
            flag: --outputTransform %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
            flag: --outputTransformType %s
    referenceVolume: (an existing file name)
            flag: --referenceVolume %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    displacementVolume: (an existing file name)
    outputTransform: (an existing file name)

## BRAINSTrimForegroundInDirection

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    BackgroundFillValue: (a unicode string)
            Fill the background of image with specified short int value. Enter
            number or use BIGNEG for a large negative number.
            flag: --BackgroundFillValue %s
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    closingSize: (an integer (int or long))
            , This is a parameter to FindLargestForegroundFilledMask,
            flag: --closingSize %d
    directionCode: (an integer (int or long))
            , This flag chooses which dimension to compare. The sign lets you
            flip direction.,
            flag: --directionCode %d
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    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.,
            flag: --headSizeLimit %f
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputVolume: (an existing file name)
            Input image to trim off the neck (and also air-filling noise.)
            flag: --inputVolume %s
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    otsuPercentileThreshold: (a float)
            , This is a parameter to FindLargestForegroundFilledMask, which is
            employed to trim off air-filling noise.,
            flag: --otsuPercentileThreshold %f
    outputVolume: (a boolean or a file name)
            Output image with neck and air-filling noise trimmed isotropic image
            with AC at center of image.
            flag: --outputVolume %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputVolume: (an existing file name)
            Output image with neck and air-filling noise trimmed isotropic image
            with AC at center of image.

## CleanUpOverlapLabels

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputBinaryVolumes: (a list of items which are an existing file name)
            The list of binary images to be checked and cleaned up. Order is
            important. Binary volume given first always wins out.
            flag: --inputBinaryVolumes %s...
    outputBinaryVolumes: (a boolean or a list of items which are a file
             name)
            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
            flag: --outputBinaryVolumes %s...
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputBinaryVolumes: (a list of items which are an existing file
             name)
            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

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    axis: (an integer (int or long))
            flag: --axis %d
    backgroundValue: (an integer (int or long))
            flag: --backgroundValue %d
    clippedImageMask: (a boolean or a file name)
            flag: --clippedImageMask %s
    closingSize: (an integer (int or long))
            flag: --closingSize %d
    debugAfterGridComputationsForegroundImage: (a boolean or a file name)
            flag: --debugAfterGridComputationsForegroundImage %s
    debugClippedImageMask: (a boolean or a file name)
            flag: --debugClippedImageMask %s
    debugDistanceImage: (a boolean or a file name)
            flag: --debugDistanceImage %s
    debugGridImage: (a boolean or a file name)
            flag: --debugGridImage %s
    debugTrimmedImage: (a boolean or a file name)
            flag: --debugTrimmedImage %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    generateDebugImages: (a boolean)
            flag: --generateDebugImages
    headSizeEstimate: (a float)
            flag: --headSizeEstimate %f
    headSizeLimit: (a float)
            flag: --headSizeLimit %f
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    imageMask: (an existing file name)
            flag: --imageMask %s
    inputVolume: (an existing file name)
            The image in which to find the center.
            flag: --inputVolume %s
    maximize: (a boolean)
            flag: --maximize
    otsuPercentileThreshold: (a float)
            flag: --otsuPercentileThreshold %f
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    clippedImageMask: (an existing file name)
    debugAfterGridComputationsForegroundImage: (an existing file name)
    debugClippedImageMask: (an existing file name)
    debugDistanceImage: (an existing file name)
    debugGridImage: (an existing file name)
    debugTrimmedImage: (an existing file name)

## GenerateLabelMapFromProbabilityMap

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputVolumes: (a list of items which are an existing file name)
            The Input probaiblity images to be computed for lable maps
            flag: --inputVolumes %s...
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    outputLabelVolume: (a boolean or a file name)
            The Input binary image for region of interest
            flag: --outputLabelVolume %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputLabelVolume: (an existing file name)
            The Input binary image for region of interest

## ImageRegionPlotter

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputBinaryROIVolume: (an existing file name)
            The Input binary image for region of interest
            flag: --inputBinaryROIVolume %s
    inputLabelVolume: (an existing file name)
            The Label Image
            flag: --inputLabelVolume %s
    inputVolume1: (an existing file name)
            The Input image to be computed for statistics
            flag: --inputVolume1 %s
    inputVolume2: (an existing file name)
            The Input image to be computed for statistics
            flag: --inputVolume2 %s
    numberOfHistogramBins: (an integer (int or long))
             the number of histogram levels
            flag: --numberOfHistogramBins %d
    outputJointHistogramData: (a unicode string)
             output data file name
            flag: --outputJointHistogramData %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    useIntensityForHistogram: (a boolean)
             Create Intensity Joint Histogram instead of Quantile Joint
            Histogram
            flag: --useIntensityForHistogram
    useROIAUTO: (a boolean)
             Use ROIAUTO to compute region of interest. This cannot be used with
            inputLabelVolume
            flag: --useROIAUTO
    verbose: (a boolean)
             print debugging information,
            flag: --verbose

Outputs:

    None

## JointHistogram

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputMaskVolumeInXAxis: (an existing file name)
            Input mask volume for inputVolumeInXAxis. Histogram will be computed
            just for the masked region
            flag: --inputMaskVolumeInXAxis %s
    inputMaskVolumeInYAxis: (an existing file name)
            Input mask volume for inputVolumeInYAxis. Histogram will be computed
            just for the masked region
            flag: --inputMaskVolumeInYAxis %s
    inputVolumeInXAxis: (an existing file name)
            The Input image to be computed for statistics
            flag: --inputVolumeInXAxis %s
    inputVolumeInYAxis: (an existing file name)
            The Input image to be computed for statistics
            flag: --inputVolumeInYAxis %s
    outputJointHistogramImage: (a unicode string)
             output joint histogram image file name. Histogram is usually 2D
            image.
            flag: --outputJointHistogramImage %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    verbose: (a boolean)
             print debugging information,
            flag: --verbose

Outputs:

    None

## ShuffleVectorsModule

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputVectorFileBaseName: (an existing file name)
            input vector file name prefix. Usually end with .txt and header file
            has prost fix of .txt.hdr
            flag: --inputVectorFileBaseName %s
    outputVectorFileBaseName: (a boolean or a file name)
            output vector file name prefix. Usually end with .txt and header
            file has prost fix of .txt.hdr
            flag: --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.
            flag: --resampleProportion %f
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputVectorFileBaseName: (an existing file name)
            output vector file name prefix. Usually end with .txt and header
            file has prost fix of .txt.hdr

## fcsv_to_hdf5

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    landmarkGlobPattern: (a unicode string)
            Glob pattern to select fcsv files
            flag: --landmarkGlobPattern %s
    landmarkTypesList: (an existing file name)
            , file containing list of landmark types,
            flag: --landmarkTypesList %s
    landmarksInformationFile: (a boolean or a file name)
            , name of HDF5 file to write matrices into,
            flag: --landmarksInformationFile %s
    modelFile: (a boolean or a file name)
            , name of HDF5 file containing BRAINSConstellationDetector Model
            file (LLSMatrices, LLSMeans and LLSSearchRadii),
            flag: --modelFile %s
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    versionID: (a unicode string)
            , Current version ID. It should be match with the version of BCD
            that will be using the output model file,
            flag: --versionID %s

Outputs:

    landmarksInformationFile: (an existing file name)
            , name of HDF5 file to write matrices into,
    modelFile: (an existing file name)
            , name of HDF5 file containing BRAINSConstellationDetector Model
            file (LLSMatrices, LLSMeans and LLSSearchRadii),

## insertMidACPCpoint

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputLandmarkFile: (an existing file name)
            Input landmark file (.fcsv)
            flag: --inputLandmarkFile %s
    outputLandmarkFile: (a boolean or a file name)
            Output landmark file (.fcsv)
            flag: --outputLandmarkFile %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputLandmarkFile: (an existing file name)
            Output landmark file (.fcsv)

## landmarksConstellationAligner

Link to code

Wraps 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:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputLandmarksPaired: (an existing file name)
            Input landmark file (.fcsv)
            flag: --inputLandmarksPaired %s
    outputLandmarksPaired: (a boolean or a file name)
            Output landmark file (.fcsv)
            flag: --outputLandmarksPaired %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputLandmarksPaired: (an existing file name)
            Output landmark file (.fcsv)

## landmarksConstellationWeights

Link to code

Wraps command ** landmarksConstellationWeights **

title: Generate Landmarks Weights (BRAINS)

category: Utilities.BRAINS

description: Train up a list of Weights for the Landmarks in BRAINSConstellationDetector

Inputs:

    [Mandatory]

    [Optional]
    LLSModel: (an existing file name)
            Linear least squares model filename in HD5 format
            flag: --LLSModel %s
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputTemplateModel: (an existing file name)
            User-specified template model.,
            flag: --inputTemplateModel %s
    inputTrainingList: (an existing file name)
            , Setup file, giving all parameters for training up a Weight list
            for landmark.,
            flag: --inputTrainingList %s
    outputWeightsList: (a boolean or a file name)
            , The filename of a csv file which is a list of landmarks and their
            corresponding weights.,
            flag: --outputWeightsList %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    outputWeightsList: (an existing file name)
            , The filename of a csv file which is a list of landmarks and their
            corresponding weights.,