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# interfaces.semtools.diffusion.tractography.ukftractography

## UKFTractography

Link to code

Wraps command ** UKFTractography **

title: UKF Tractography

category: Diffusion.Tractography

description: This module traces fibers in a DWI Volume using the multiple tensor unscented Kalman Filter methology. For more informations check the documentation.

version: 1.0

documentation-url: http://www.nitrc.org/plugins/mwiki/index.php/ukftractography:MainPage

contributor: Yogesh Rathi, Stefan Lienhard, Yinpeng Li, Martin Styner, Ipek Oguz, Yundi Shi, Christian Baumgartner, Kent Williams, Hans Johnson, Peter Savadjiev, Carl-Fredrik Westin.

acknowledgements: The development of this module was supported by NIH grants R01 MH097979 (PI Rathi), R01 MH092862 (PIs Westin and Verma), U01 NS083223 (PI Westin), R01 MH074794 (PI Westin) and P41 EB015902 (PI Kikinis).

Inputs:

    [Mandatory]

    [Optional]
    Ql: (a float)
            Process noise for eigenvalues
            flag: --Ql %f
    Qm: (a float)
            Process noise for angles/direction
            flag: --Qm %f
    Qw: (a float)
            Process noise for free water weights, ignored if no free water
            estimation
            flag: --Qw %f
    Rs: (a float)
            Measurement noise
            flag: --Rs %f
    args: (a string)
            Additional parameters to the command
            flag: %s
    dwiFile: (an existing file name)
            Input DWI volume
            flag: --dwiFile %s
    environ: (a dictionary with keys which are a value of type 'str' and
             with values which are a value of type 'str', nipype default value:
             {})
            Environment variables
    freeWater: (a boolean)
            Adds a term for free water difusion to the model. (Note for experts:
            if checked, the 1T simple model is forced)
            flag: --freeWater
    fullTensorModel: (a boolean)
            Whether to use the full tensor model. If unchecked, use the default
            simple tensor model
            flag: --fullTensorModel
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    labels: (a list of items which are an integer)
            A vector of the ROI labels to be used
            flag: --labels %s
    maskFile: (an existing file name)
            Mask for diffusion tractography
            flag: --maskFile %s
    maxBranchingAngle: (a float)
            Maximum branching angle, in degrees. When using multiple tensors, a
            new branch will be created when the tensors' major directions form
            an angle between (minBranchingAngle, maxBranchingAngle). Branching
            is supressed when this maxBranchingAngle is set to 0.0
            flag: --maxBranchingAngle %f
    maxHalfFiberLength: (a float)
            The max length limit of the half fibers generated during
            tractography. Here the fiber is 'half' because the tractography goes
            in only one direction from one seed point at a time
            flag: --maxHalfFiberLength %f
    minBranchingAngle: (a float)
            Minimum branching angle, in degrees. When using multiple tensors, a
            new branch will be created when the tensors' major directions form
            an angle between (minBranchingAngle, maxBranchingAngle)
            flag: --minBranchingAngle %f
    minFA: (a float)
            Abort the tractography when the Fractional Anisotropy is less than
            this value
            flag: --minFA %f
    minGA: (a float)
            Abort the tractography when the Generalized Anisotropy is less than
            this value
            flag: --minGA %f
    numTensor: ('1' or '2')
            Number of tensors used
            flag: --numTensor %s
    numThreads: (an integer)
            Number of threads used during computation. Set to the number of
            cores on your workstation for optimal speed. If left undefined the
            number of cores detected will be used.
            flag: --numThreads %d
    recordCovariance: (a boolean)
            Whether to store the covariance. Will generate field 'covariance' in
            fiber.
            flag: --recordCovariance
    recordFA: (a boolean)
            Whether to store FA. Attaches field 'FA', and 'FA2' for 2-tensor
            case to fiber.
            flag: --recordFA
    recordFreeWater: (a boolean)
            Whether to store the fraction of free water. Attaches field
            'FreeWater' to fiber.
            flag: --recordFreeWater
    recordLength: (a float)
            Record length of tractography, in millimeters
            flag: --recordLength %f
    recordNMSE: (a boolean)
            Whether to store NMSE. Attaches field 'NMSE' to fiber.
            flag: --recordNMSE
    recordState: (a boolean)
            Whether to attach the states to the fiber. Will generate field
            'state'.
            flag: --recordState
    recordTensors: (a boolean)
            Recording the tensors enables Slicer to color the fiber bundles by
            FA, orientation, and so on. The fields will be called 'TensorN',
            where N is the tensor number.
            flag: --recordTensors
    recordTrace: (a boolean)
            Whether to store Trace. Attaches field 'Trace', and 'Trace2' for
            2-tensor case to fiber.
            flag: --recordTrace
    seedFALimit: (a float)
            Seed points whose FA are below this value are excluded
            flag: --seedFALimit %f
    seedsFile: (an existing file name)
            Seeds for diffusion. If not specified, full brain tractography will
            be performed, and the algorithm will start from every voxel in the
            brain mask where the Generalized Anisotropy is bigger than 0.18
            flag: --seedsFile %s
    seedsPerVoxel: (an integer)
             Each seed generates a fiber, thus using more seeds generates more
            fibers. In general use 1 or 2 seeds, and for a more thorough result
            use 5 or 10 (depending on your machine this may take up to 2 days to
            run).,
            flag: --seedsPerVoxel %d
    stepLength: (a float)
            Step length of tractography, in millimeters
            flag: --stepLength %f
    storeGlyphs: (a boolean)
            Store tensors' main directions as two-point lines in a separate file
            named glyphs_{tracts}. When using multiple tensors, only the major
            tensors' main directions are stored
            flag: --storeGlyphs
    terminal_output: ('stream' or 'allatonce' or 'file' or '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
    tracts: (a boolean or a file name)
            Tracts generated, with first tensor output
            flag: --tracts %s
    tractsWithSecondTensor: (a boolean or a file name)
            Tracts generated, with second tensor output (if there is one)
            flag: --tractsWithSecondTensor %s
    writeAsciiTracts: (a boolean)
            Write tract file as a VTK binary data file
            flag: --writeAsciiTracts
    writeUncompressedTracts: (a boolean)
            Write tract file as a VTK uncompressed data file
            flag: --writeUncompressedTracts

Outputs:

    tracts: (an existing file name)
            Tracts generated, with first tensor output
    tractsWithSecondTensor: (an existing file name)
            Tracts generated, with second tensor output (if there is one)