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# interfaces.semtools.segmentation.specialized

## BRAINSABC

Link to code

Wraps command ** BRAINSABC **

title: Intra-subject registration, bias Correction, and tissue classification (BRAINS)

category: Segmentation.Specialized

description: Atlas-based tissue segmentation method. This is an algorithmic extension of work done by XXXX at UNC and Utah XXXX need more description here.

Inputs:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    atlasDefinition: (an existing file name)
            Contains all parameters for Atlas
            flag: --atlasDefinition %s
    atlasToSubjectInitialTransform: (a boolean or a file name)
            The initial transform from atlas to the subject
            flag: --atlasToSubjectInitialTransform %s
    atlasToSubjectTransform: (a boolean or a file name)
            The transform from atlas to the subject
            flag: --atlasToSubjectTransform %s
    atlasToSubjectTransformType: ('Identity' or 'Rigid' or 'Affine' or
             'BSpline' or 'SyN')
             What type of linear transform type do you want to use to register
            the atlas to the reference subject image.
            flag: --atlasToSubjectTransformType %s
    atlasWarpingOff: (a boolean)
            Deformable registration of atlas to subject
            flag: --atlasWarpingOff
    debuglevel: (an integer (int or long))
            Display debug messages, and produce debug intermediate results.
            0=OFF, 1=Minimal, 10=Maximum debugging.
            flag: --debuglevel %d
    defaultSuffix: (a unicode string)
            flag: --defaultSuffix %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
    filterIteration: (an integer (int or long))
            Filter iterations
            flag: --filterIteration %d
    filterMethod: ('None' or 'CurvatureFlow' or
             'GradientAnisotropicDiffusion' or 'Median')
            Filter method for preprocessing of registration
            flag: --filterMethod %s
    filterTimeStep: (a float)
            Filter time step should be less than (PixelSpacing/(1^(DIM+1)),
            value is set to negative, then allow automatic setting of this
            value.
            flag: --filterTimeStep %f
    gridSize: (a list of items which are an integer (int or long))
            Grid size for atlas warping with BSplines
            flag: --gridSize %s
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    implicitOutputs: (a boolean or a list of items which are a file name)
            Outputs to be made available to NiPype. Needed because not all
            BRAINSABC outputs have command line arguments.
            flag: --implicitOutputs %s...
    inputVolumeTypes: (a list of items which are a unicode string)
            The list of input image types corresponding to the inputVolumes.
            flag: --inputVolumeTypes %s
    inputVolumes: (a list of items which are an existing file name)
            The list of input image files to be segmented.
            flag: --inputVolumes %s...
    interpolationMode: ('BSpline' or 'NearestNeighbor' or 'WindowedSinc'
             or 'Linear' or 'ResampleInPlace' 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, NearestNeighbor, BSpline, WindowedSinc,
            or ResampleInPlace. The ResampleInPlace option will create an image
            with the same discrete voxel values and will adjust the origin and
            direction of the physical space interpretation.
            flag: --interpolationMode %s
    maxBiasDegree: (an integer (int or long))
            Maximum bias degree
            flag: --maxBiasDegree %d
    maxIterations: (an integer (int or long))
            Filter iterations
            flag: --maxIterations %d
    medianFilterSize: (a list of items which are an integer (int or
             long))
            The radius for the optional MedianImageFilter preprocessing in all 3
            directions.
            flag: --medianFilterSize %s
    numberOfSubSamplesInEachPlugArea: (a list of items which are an
             integer (int or long))
            Number of continous index samples taken at each direction of lattice
            space for each plug volume.
            flag: --numberOfSubSamplesInEachPlugArea %s
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    outputDir: (a boolean or a directory name)
            Ouput directory
            flag: --outputDir %s
    outputDirtyLabels: (a boolean or a file name)
            Output Dirty Label Image
            flag: --outputDirtyLabels %s
    outputFormat: ('NIFTI' or 'Meta' or 'Nrrd')
            Output format
            flag: --outputFormat %s
    outputLabels: (a boolean or a file name)
            Output Label Image
            flag: --outputLabels %s
    outputVolumes: (a boolean or a list of items which are a file name)
            Corrected Output Images: should specify the same number of images as
            inputVolume, if only one element is given, then it is used as a file
            pattern where %s is replaced by the imageVolumeType, and %d by the
            index list location.
            flag: --outputVolumes %s...
    posteriorTemplate: (a unicode string)
            filename template for Posterior output files
            flag: --posteriorTemplate %s
    purePlugsThreshold: (a float)
            If this threshold value is greater than zero, only pure samples are
            used to compute the distributions in EM classification, and only
            pure samples are used for KNN training. The default value is set to
            0, that means not using pure plugs. However, a value of 0.2 is
            suggested if you want to activate using pure plugs option.
            flag: --purePlugsThreshold %f
    restoreState: (an existing file name)
            The initial state for the registration process
            flag: --restoreState %s
    saveState: (a boolean or a file name)
            (optional) Filename to which save the final state of the
            registration
            flag: --saveState %s
    subjectIntermodeTransformType: ('Identity' or 'Rigid' or 'Affine' or
             'BSpline')
             What type of linear transform type do you want to use to register
            the atlas to the reference subject image.
            flag: --subjectIntermodeTransformType %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
    useKNN: (a boolean)
            Use the KNN stage of estimating posteriors.
            flag: --useKNN
    writeLess: (a boolean)
            Does not write posteriors and filtered, bias corrected images
            flag: --writeLess

Outputs:

    atlasToSubjectInitialTransform: (an existing file name)
            The initial transform from atlas to the subject
    atlasToSubjectTransform: (an existing file name)
            The transform from atlas to the subject
    implicitOutputs: (a list of items which are an existing file name)
            Outputs to be made available to NiPype. Needed because not all
            BRAINSABC outputs have command line arguments.
    outputDir: (an existing directory name)
            Ouput directory
    outputDirtyLabels: (an existing file name)
            Output Dirty Label Image
    outputLabels: (an existing file name)
            Output Label Image
    outputVolumes: (a list of items which are an existing file name)
            Corrected Output Images: should specify the same number of images as
            inputVolume, if only one element is given, then it is used as a file
            pattern where %s is replaced by the imageVolumeType, and %d by the
            index list location.
    saveState: (an existing file name)
            (optional) Filename to which save the final state of the
            registration

## BRAINSConstellationDetector

Link to code

Wraps command ** BRAINSConstellationDetector **

title: Brain Landmark Constellation Detector (BRAINS)

category: Segmentation.Specialized

description: This program will find the mid-sagittal plane, a constellation of landmarks in a volume, and create an AC/PC aligned data set with the AC point at the center of the voxel lattice (labeled at the origin of the image physical space.) Part of this work is an extention of the algorithms originally described by Dr. Babak A. Ardekani, Alvin H. Bachman, Model-based automatic detection of the anterior and posterior commissures on MRI scans, NeuroImage, Volume 46, Issue 3, 1 July 2009, Pages 677-682, ISSN 1053-8119, DOI: 10.1016/j.neuroimage.2009.02.030. (http://www.sciencedirect.com/science/article/B6WNP-4VRP25C-4/2/8207b962a38aa83c822c6379bc43fe4c)

version: 1.0

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

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
    LLSModel: (an existing file name)
            Linear least squares model filename in HD5 format
            flag: --LLSModel %s
    acLowerBound: (a float)
            , When generating a resampled output image, replace the image with
            the BackgroundFillValue everywhere below the plane This Far in
            physical units (millimeters) below (inferior to) the AC point (as
            found by the model.) 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
    atlasLandmarkWeights: (an existing file name)
            Weights associated with atlas landmarks to be used for BRAINSFit
            registration initialization,
            flag: --atlasLandmarkWeights %s
    atlasLandmarks: (an existing file name)
            Atlas landmarks to be used for BRAINSFit registration
            initialization,
            flag: --atlasLandmarks %s
    atlasVolume: (an existing file name)
            Atlas volume image to be used for BRAINSFit registration
            flag: --atlasVolume %s
    cutOutHeadInOutputVolume: (a boolean)
            , Flag to cut out just the head tissue when producing an
            (un)transformed clipped volume.,
            flag: --cutOutHeadInOutputVolume
    debug: (a boolean)
            , Show internal debugging information.,
            flag: --debug
    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
    forceACPoint: (a list of items which are a float)
            , Use this flag to manually specify the AC point from the original
            image on the command line.,
            flag: --forceACPoint %s
    forceHoughEyeDetectorReportFailure: (a boolean)
            , Flag indicates whether the Hough eye detector should report
            failure,
            flag: --forceHoughEyeDetectorReportFailure
    forcePCPoint: (a list of items which are a float)
            , Use this flag to manually specify the PC point from the original
            image on the command line.,
            flag: --forcePCPoint %s
    forceRPPoint: (a list of items which are a float)
            , Use this flag to manually specify the RP point from the original
            image on the command line.,
            flag: --forceRPPoint %s
    forceVN4Point: (a list of items which are a float)
            , Use this flag to manually specify the VN4 point from the original
            image on the command line.,
            flag: --forceVN4Point %s
    houghEyeDetectorMode: (an integer (int or long))
            , This flag controls the mode of Hough eye detector. By default,
            value of 1 is for T1W images, while the value of 0 is for T2W and PD
            images.,
            flag: --houghEyeDetectorMode %d
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inputLandmarksEMSP: (an existing file name)
            , The filename for the new subject-specific landmark definition file
            in the same format produced by Slicer3 (in .fcsv) with the landmarks
            in the estimated MSP aligned space to be loaded. The detector will
            only process landmarks not enlisted on the file.,
            flag: --inputLandmarksEMSP %s
    inputTemplateModel: (an existing file name)
            User-specified template model.,
            flag: --inputTemplateModel %s
    inputVolume: (an existing file name)
            Input image in which to find ACPC points
            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), NOTE: -1= Prealigned so no
            estimate!.,
            flag: --mspQualityLevel %d
    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 when acLowerBound is set and an
            outputUntransformedClippedVolume is requested.,
            flag: --otsuPercentileThreshold %f
    outputLandmarksInACPCAlignedSpace: (a boolean or a file name)
            , The filename for the new subject-specific landmark definition file
            in the same format produced by Slicer3 (.fcsv) with the landmarks in
            the output image space (the detected RP, AC, PC, and VN4) in it to
            be written.,
            flag: --outputLandmarksInACPCAlignedSpace %s
    outputLandmarksInInputSpace: (a boolean or a file name)
            , The filename for the new subject-specific landmark definition file
            in the same format produced by Slicer3 (.fcsv) with the landmarks in
            the original image space (the detected RP, AC, PC, and VN4) in it to
            be written.,
            flag: --outputLandmarksInInputSpace %s
    outputMRML: (a boolean or a file name)
            , The filename for the new subject-specific scene definition file in
            the same format produced by Slicer3 (in .mrml format). Only the
            components that were specified by the user on command line would be
            generated. Compatible components include inputVolume, outputVolume,
            outputLandmarksInInputSpace, outputLandmarksInACPCAlignedSpace, and
            outputTransform.,
            flag: --outputMRML %s
    outputResampledVolume: (a boolean or a file name)
            ACPC-aligned output image in a resampled unifor space. Currently
            this is a 1mm, 256^3, Identity direction image.
            flag: --outputResampledVolume %s
    outputTransform: (a boolean or a file name)
            The filename for the original space to ACPC alignment to be written
            (in .h5 format).,
            flag: --outputTransform %s
    outputUntransformedClippedVolume: (a boolean or a file name)
            Output image in which to store neck-clipped input image, with the
            use of --acLowerBound and maybe --cutOutHeadInUntransformedVolume.
            flag: --outputUntransformedClippedVolume %s
    outputVerificationScript: (a boolean or a file name)
            , The filename for the Slicer3 script that verifies the aligned
            landmarks against the aligned image file. This will happen only in
            conjunction with saveOutputLandmarks and an outputVolume.,
            flag: --outputVerificationScript %s
    outputVolume: (a boolean or a file name)
            ACPC-aligned output image with the same voxels, but updated origin,
            and direction cosign so that the AC point would fall at the physical
            location (0.0,0.0,0.0), and the mid-sagital plane is the plane where
            physical L/R coordinate is 0.0.
            flag: --outputVolume %s
    rVN4: (a float)
            , Search radius for VN4 in unit of mm,
            flag: --rVN4 %f
    rac: (a float)
            , Search radius for AC in unit of mm,
            flag: --rac %f
    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 debuging images to be written.,
            flag: --resultsDir %s
    rmpj: (a float)
            , Search radius for MPJ in unit of mm,
            flag: --rmpj %f
    rpc: (a float)
            , Search radius for PC in unit of mm,
            flag: --rpc %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
    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
    writeBranded2DImage: (a boolean or a file name)
            , The filename for the 2D .png branded midline debugging image. This
            will happen only in conjunction with requesting an outputVolume.,
            flag: --writeBranded2DImage %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.,
            flag: --writedebuggingImagesLevel %d

Outputs:

    outputLandmarksInACPCAlignedSpace: (an existing file name)
            , The filename for the new subject-specific landmark definition file
            in the same format produced by Slicer3 (.fcsv) with the landmarks in
            the output image space (the detected RP, AC, PC, and VN4) in it to
            be written.,
    outputLandmarksInInputSpace: (an existing file name)
            , The filename for the new subject-specific landmark definition file
            in the same format produced by Slicer3 (.fcsv) with the landmarks in
            the original image space (the detected RP, AC, PC, and VN4) in it to
            be written.,
    outputMRML: (an existing file name)
            , The filename for the new subject-specific scene definition file in
            the same format produced by Slicer3 (in .mrml format). Only the
            components that were specified by the user on command line would be
            generated. Compatible components include inputVolume, outputVolume,
            outputLandmarksInInputSpace, outputLandmarksInACPCAlignedSpace, and
            outputTransform.,
    outputResampledVolume: (an existing file name)
            ACPC-aligned output image in a resampled unifor space. Currently
            this is a 1mm, 256^3, Identity direction image.
    outputTransform: (an existing file name)
            The filename for the original space to ACPC alignment to be written
            (in .h5 format).,
    outputUntransformedClippedVolume: (an existing file name)
            Output image in which to store neck-clipped input image, with the
            use of --acLowerBound and maybe --cutOutHeadInUntransformedVolume.
    outputVerificationScript: (an existing file name)
            , The filename for the Slicer3 script that verifies the aligned
            landmarks against the aligned image file. This will happen only in
            conjunction with saveOutputLandmarks and an outputVolume.,
    outputVolume: (an existing file name)
            ACPC-aligned output image with the same voxels, but updated origin,
            and direction cosign so that the AC point would fall at the physical
            location (0.0,0.0,0.0), and the mid-sagital plane is the plane where
            physical L/R coordinate is 0.0.
    resultsDir: (an existing directory name)
            , The directory for the debuging images to be written.,
    writeBranded2DImage: (an existing file name)
            , The filename for the 2D .png branded midline debugging image. This
            will happen only in conjunction with requesting an outputVolume.,

## BRAINSCreateLabelMapFromProbabilityMaps

Link to code

Wraps command ** BRAINSCreateLabelMapFromProbabilityMaps **

title: Create Label Map From Probability Maps (BRAINS)

category: Segmentation.Specialized

description: Given A list of Probability Maps, generate a LabelMap.

Inputs:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    cleanLabelVolume: (a boolean or a file name)
            the foreground labels volume
            flag: --cleanLabelVolume %s
    dirtyLabelVolume: (a boolean or a file name)
            the labels prior to cleaning
            flag: --dirtyLabelVolume %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
    foregroundPriors: (a list of items which are an integer (int or
             long))
            A list: For each Prior Label, 1 if foreground, 0 if background
            flag: --foregroundPriors %s
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    inclusionThreshold: (a float)
            tolerance for inclusion
            flag: --inclusionThreshold %f
    inputProbabilityVolume: (a list of items which are an existing file
             name)
            The list of proobabilityimages.
            flag: --inputProbabilityVolume %s...
    nonAirRegionMask: (an existing file name)
            a mask representing the 'NonAirRegion' -- Just force pixels in this
            region to zero
            flag: --nonAirRegionMask %s
    priorLabelCodes: (a list of items which are an integer (int or long))
            A list of PriorLabelCode values used for coding the output label
            images
            flag: --priorLabelCodes %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:

    cleanLabelVolume: (an existing file name)
            the foreground labels volume
    dirtyLabelVolume: (an existing file name)
            the labels prior to cleaning

## BRAINSCut

Link to code

Wraps command ** BRAINSCut **

title: BRAINSCut (BRAINS)

category: Segmentation.Specialized

description: Automatic Segmentation using neural networks

version: 1.0

license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt

contributor: Vince Magnotta, Hans Johnson, Greg Harris, Kent Williams, Eunyoung Regina Kim

Inputs:

    [Mandatory]

    [Optional]
    NoTrainingVectorShuffling: (a boolean)
            If this flag is on, there will be no shuffling.
            flag: --NoTrainingVectorShuffling
    applyModel: (a boolean)
            apply the neural net
            flag: --applyModel
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    computeSSEOn: (a boolean)
            compute Sum of Square Error (SSE) along the trained model until the
            number of iteration given in the modelConfigurationFilename file
            flag: --computeSSEOn
    createVectors: (a boolean)
            create vectors for training neural net
            flag: --createVectors
    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
    generateProbability: (a boolean)
            Generate probability map
            flag: --generateProbability
    histogramEqualization: (a boolean)
            A Histogram Equalization process could be added to the
            creating/applying process from Subject To Atlas. Default is false,
            which genreate input vectors without Histogram Equalization.
            flag: --histogramEqualization
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    method: ('RandomForest' or 'ANN')
            flag: --method %s
    modelConfigurationFilename: (an existing file name)
            XML File defining BRAINSCut parameters
            flag: --modelConfigurationFilename %s
    modelFilename: (a unicode string)
             model file name given from user (not by xml configuration file)
            flag: --modelFilename %s
    multiStructureThreshold: (a boolean)
            multiStructureThreshold module to deal with overlaping area
            flag: --multiStructureThreshold
    netConfiguration: (an existing file name)
            XML File defining BRAINSCut parameters. OLD NAME. PLEASE USE
            modelConfigurationFilename instead.
            flag: --netConfiguration %s
    numberOfTrees: (an integer (int or long))
             Random tree: number of trees. This is to be used when only one
            model with specified depth wish to be created.
            flag: --numberOfTrees %d
    randomTreeDepth: (an integer (int or long))
             Random tree depth. This is to be used when only one model with
            specified depth wish to be created.
            flag: --randomTreeDepth %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
    trainModel: (a boolean)
            train the neural net
            flag: --trainModel
    trainModelStartIndex: (an integer (int or long))
            Starting iteration for training
            flag: --trainModelStartIndex %d
    validate: (a boolean)
            validate data set.Just need for the first time run ( This is for
            validation of xml file and not working yet )
            flag: --validate
    verbose: (an integer (int or long))
            print out some debugging information
            flag: --verbose %d

Outputs:

    None

## BRAINSMultiSTAPLE

Link to code

Wraps command ** BRAINSMultiSTAPLE **

title: Create best representative label map)

category: Segmentation.Specialized

description: given a list of label map images, create a representative/average label map.

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
    inputCompositeT1Volume: (an existing file name)
            Composite T1, all label maps transofrmed into the space for this
            image.
            flag: --inputCompositeT1Volume %s
    inputLabelVolume: (a list of items which are an existing file name)
            The list of proobabilityimages.
            flag: --inputLabelVolume %s...
    inputTransform: (a list of items which are an existing file name)
            transforms to apply to label volumes
            flag: --inputTransform %s...
    labelForUndecidedPixels: (an integer (int or long))
            Label for undecided pixels
            flag: --labelForUndecidedPixels %d
    outputConfusionMatrix: (a boolean or a file name)
            Confusion Matrix
            flag: --outputConfusionMatrix %s
    outputMultiSTAPLE: (a boolean or a file name)
            the MultiSTAPLE average of input label volumes
            flag: --outputMultiSTAPLE %s
    resampledVolumePrefix: (a unicode string)
            if given, write out resampled volumes with this prefix
            flag: --resampledVolumePrefix %s
    skipResampling: (a boolean)
            Omit resampling images into reference space
            flag: --skipResampling
    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:

    outputConfusionMatrix: (an existing file name)
            Confusion Matrix
    outputMultiSTAPLE: (an existing file name)
            the MultiSTAPLE average of input label volumes

## BRAINSROIAuto

Link to code

Wraps command ** BRAINSROIAuto **

title: Foreground masking (BRAINS)

category: Segmentation.Specialized

description: This program is used to create a mask over the most prominant forground region in an image. This is accomplished via a combination of otsu thresholding and a closing operation. More documentation is available here: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/ForegroundMasking.

version: 2.4.1

license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt

contributor: Hans J. Johnson, hans-johnson -at- uiowa.edu, http://www.psychiatry.uiowa.edu

acknowledgements: Hans Johnson(1,3,4); Kent Williams(1); Gregory Harris(1), Vincent Magnotta(1,2,3); Andriy Fedorov(5), fedorov -at- bwh.harvard.edu (Slicer integration); (1=University of Iowa Department of Psychiatry, 2=University of Iowa Department of Radiology, 3=University of Iowa Department of Biomedical Engineering, 4=University of Iowa Department of Electrical and Computer Engineering, 5=Surgical Planning Lab, Harvard)

Inputs:

    [Mandatory]

    [Optional]
    ROIAutoDilateSize: (a float)
            This flag is only relavent when using ROIAUTO mode for initializing
            masks. It defines the final dilation size to capture a bit of
            background outside the tissue region. At setting of 10mm has been
            shown to help regularize a BSpline registration type so that there
            is some background constraints to match the edges of the head
            better.
            flag: --ROIAutoDilateSize %f
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    closingSize: (a float)
            The Closing Size (in millimeters) for largest connected filled mask.
            This value is divided by image spacing and rounded to the next
            largest voxel number.
            flag: --closingSize %f
    cropOutput: (a boolean)
            The inputVolume cropped to the region of the ROI mask.
            flag: --cropOutput
    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 image for finding the largest region filled mask.
            flag: --inputVolume %s
    maskOutput: (a boolean)
            The inputVolume multiplied by the ROI mask.
            flag: --maskOutput
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    otsuPercentileThreshold: (a float)
            Parameter to the Otsu threshold algorithm.
            flag: --otsuPercentileThreshold %f
    outputROIMaskVolume: (a boolean or a file name)
            The ROI automatically found from the input image.
            flag: --outputROIMaskVolume %s
    outputVolume: (a boolean or a file name)
            The inputVolume with optional [maskOutput|cropOutput] to the region
            of the brain mask.
            flag: --outputVolume %s
    outputVolumePixelType: ('float' or 'short' or 'ushort' or 'int' or
             'uint' or 'uchar')
            The output image Pixel Type is the scalar datatype for
            representation of the Output Volume.
            flag: --outputVolumePixelType %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
    thresholdCorrectionFactor: (a float)
            A factor to scale the Otsu algorithm's result threshold, in case
            clipping mangles the image.
            flag: --thresholdCorrectionFactor %f

Outputs:

    outputROIMaskVolume: (an existing file name)
            The ROI automatically found from the input image.
    outputVolume: (an existing file name)
            The inputVolume with optional [maskOutput|cropOutput] to the region
            of the brain mask.

## BinaryMaskEditorBasedOnLandmarks

Link to code

Wraps command ** BinaryMaskEditorBasedOnLandmarks **

title: BRAINS Binary Mask Editor Based On Landmarks(BRAINS)

category: Segmentation.Specialized

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
    inputBinaryVolume: (an existing file name)
            Input binary image in which to be edited
            flag: --inputBinaryVolume %s
    inputLandmarkNames: (a list of items which are a unicode string)
             A target input landmark name to be edited. This should be listed in
            the inputLandmakrFilename Given.
            flag: --inputLandmarkNames %s
    inputLandmarkNamesForObliquePlane: (a list of items which are a
             unicode string)
             Three subset landmark names of inputLandmarksFilename for a oblique
            plane computation. The plane computed for binary volume editing.
            flag: --inputLandmarkNamesForObliquePlane %s
    inputLandmarksFilename: (an existing file name)
             The filename for the landmark definition file in the same format
            produced by Slicer3 (.fcsv).
            flag: --inputLandmarksFilename %s
    outputBinaryVolume: (a boolean or a file name)
            Output binary image in which to be edited
            flag: --outputBinaryVolume %s
    setCutDirectionForLandmark: (a list of items which are a unicode
             string)
            Setting the cutting out direction of the input binary image to the
            one of anterior, posterior, left, right, superior or posterior.
            (ENUMERATION: ANTERIOR, POSTERIOR, LEFT, RIGHT, SUPERIOR, POSTERIOR)
            flag: --setCutDirectionForLandmark %s
    setCutDirectionForObliquePlane: (a list of items which are a unicode
             string)
            If this is true, the mask will be thresholded out to the direction
            of inferior, posterior, and/or left. Default behavrior is that
            cutting out to the direction of superior, anterior and/or right.
            flag: --setCutDirectionForObliquePlane %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:

    outputBinaryVolume: (an existing file name)
            Output binary image in which to be edited

## ESLR

Link to code

Wraps command ** ESLR **

title: Clean Contiguous Label Map (BRAINS)

category: Segmentation.Specialized

description: From a range of label map values, extract the largest contiguous region of those labels

Inputs:

    [Mandatory]

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    closingSize: (an integer (int or long))
            The closing size for hole filling.
            flag: --closingSize %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
    high: (an integer (int or long))
            The higher bound of the labels to be used.
            flag: --high %d
    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 Label Volume
            flag: --inputVolume %s
    low: (an integer (int or long))
            The lower bound of the labels to be used.
            flag: --low %d
    numberOfThreads: (an integer (int or long))
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    openingSize: (an integer (int or long))
            The opening size for hole filling.
            flag: --openingSize %d
    outputVolume: (a boolean or a file name)
            Output Label Volume
            flag: --outputVolume %s
    preserveOutside: (a boolean)
            For values outside the specified range, preserve those values.
            flag: --preserveOutside
    safetySize: (an integer (int or long))
            The safetySize size for the clipping region.
            flag: --safetySize %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:

    outputVolume: (an existing file name)
            Output Label Volume