.. AUTO-GENERATED FILE -- DO NOT EDIT!

interfaces.slicer.registration
==============================


.. _nipype.interfaces.slicer.registration.BRAINSDemonWarp:


.. index:: BRAINSDemonWarp

BRAINSDemonWarp
---------------

Code: http://github.com/nipy/nipype/blob/master/nipype/interfaces/slicer/registration.py#L280

Wraps command ** BRAINSDemonWarp **

title: Demon Registration (BRAINS)

category: Registration

description:
    This program finds a deformation field to warp a moving image onto a fixed image.  The images must be of the same signal kind, and contain an image of the same kind of object.  This program uses the Thirion Demons warp software in ITK, the Insight Toolkit.  Additional information is available at: http://www.nitrc.org/projects/brainsdemonwarp.



version: 3.0.0

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Modules:BRAINSDemonWarp

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

contributor: This tool was developed by Hans J. Johnson and Greg Harris.

acknowledgements: The development of this tool was supported by funding from grants NS050568 and NS40068 from the National Institute of Neurological Disorders and Stroke and grants MH31593, MH40856, from the National Institute of Mental Health.

Inputs::

        [Mandatory]

        [Optional]
        args: (a string)
                Additional parameters to the command
        arrayOfPyramidLevelIterations: (an integer)
                The number of iterations for each pyramid level
        backgroundFillValue: (an integer)
                Replacement value to overwrite background when performing BOBF
        checkerboardPatternSubdivisions: (an integer)
                Number of Checkerboard subdivisions in all 3 directions
        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
        fixedBinaryVolume: (an existing file name)
                Mask filename for desired region of interest in the Fixed image.
        fixedVolume: (an existing file name)
                Required: input fixed (target) image
        gradient_type: ('0' or '1' or '2')
                Type of gradient used for computing the demons force (0 is symmetrized, 1 is fixed
                image, 2 is moving image)
        gui: (a boolean)
                Display intermediate image volumes for debugging
        histogramMatch: (a boolean)
                Histogram Match the input images.  This is suitable for images of the same modality that
                may have different absolute scales, but the same overall intensity profile.
        ignore_exception: (a boolean, nipype default value: False)
                Print an error message instead of throwing an exception in case the interface fails to
                run
        initializeWithDeformationField: (an existing file name)
                Initial deformation field vector image file name
        initializeWithTransform: (an existing file name)
                Initial Transform filename
        inputPixelType: ('float' or 'short' or 'ushort' or 'int' or 'uchar')
                Input volumes will be typecast to this format: float|short|ushort|int|uchar
        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
        lowerThresholdForBOBF: (an integer)
                Lower threshold for performing BOBF
        maskProcessingMode: ('NOMASK' or 'ROIAUTO' or 'ROI' or 'BOBF')
                What mode to use for using the masks: NOMASK|ROIAUTO|ROI|BOBF.  If ROIAUTO is choosen,
                then the mask is implicitly defined using a otsu forground and hole filling algorithm.
                Where the Region Of Interest mode uses the masks to define what parts of the image
                should be used for computing the deformation field.  Brain Only Background Fill uses the
                masks to pre-process the input images by clipping and filling in the background with a
                predefined value.
        max_step_length: (a float)
                Maximum length of an update vector (0: no restriction)
        medianFilterSize: (an integer)
                Median filter radius in all 3 directions.  When images have a lot of salt and pepper
                noise, this step can improve the registration.
        minimumFixedPyramid: (an integer)
                The shrink factor for the first level of the fixed image pyramid. (i.e. start at 1/16
                scale, then 1/8, then 1/4, then 1/2, and finally full scale)
        minimumMovingPyramid: (an integer)
                The shrink factor for the first level of the moving image pyramid. (i.e. start at 1/16
                scale, then 1/8, then 1/4, then 1/2, and finally full scale)
        movingBinaryVolume: (an existing file name)
                Mask filename for desired region of interest in the Moving image.
        movingVolume: (an existing file name)
                Required: input moving image
        neighborhoodForBOBF: (an integer)
                neighborhood in all 3 directions to be included when performing BOBF
        numberOfBCHApproximationTerms: (an integer)
                Number of terms in the BCH expansion
        numberOfHistogramBins: (an integer)
                The number of histogram levels
        numberOfMatchPoints: (an integer)
                The number of match points for histrogramMatch
        numberOfPyramidLevels: (an integer)
                Number of image pyramid levels to use in the multi-resolution registration.
        numberOfThreads: (an integer)
                Explicitly specify the maximum number of threads to use.
        outputCheckerboardVolume: (a boolean or a file name)
                Genete a checkerboard image volume between the fixedVolume and the deformed
                movingVolume.
        outputDebug: (a boolean)
                Flag to write debugging images after each step.
        outputDeformationFieldVolume: (a boolean or a file name)
                Output deformation field vector image (will have the same physical space as the
                fixedVolume).
        outputDisplacementFieldPrefix: (a string)
                Displacement field filename prefix for writing separate x, y, and z component images
        outputNormalized: (a boolean)
                Flag to warp and write the normalized images to output.  In normalized images the image
                values are fit-scaled to be between 0 and the maximum storage type value.
        outputPixelType: ('float' or 'short' or 'ushort' or 'int' or 'uchar')
                outputVolume will be typecast to this format: float|short|ushort|int|uchar
        outputVolume: (a boolean or a file name)
                Required: output resampled moving image (will have the same physical space as the
                fixedVolume).
        promptUser: (a boolean)
                Prompt the user to hit enter each time an image is sent to the DebugImageViewer
        registrationFilterType: ('Demons' or 'FastSymmetricForces' or 'Diffeomorphic' or
                 'LogDemons' or 'SymmetricLogDemons')
                Registration Filter Type:
                Demons|FastSymmetricForces|Diffeomorphic|LogDemons|SymmetricLogDemons
        seedForBOBF: (an integer)
                coordinates in all 3 directions for Seed when performing BOBF
        smoothDeformationFieldSigma: (a float)
                A gaussian smoothing value to be applied to the deformation feild at each iteration.
        upFieldSmoothing: (a float)
                Smoothing sigma for the update field at each iteration
        upperThresholdForBOBF: (an integer)
                Upper threshold for performing BOBF
        use_vanilla_dem: (a boolean)
                Run vanilla demons algorithm

Outputs::

        outputCheckerboardVolume: (an existing file name)
                Genete a checkerboard image volume between the fixedVolume and the deformed
                movingVolume.
        outputDeformationFieldVolume: (an existing file name)
                Output deformation field vector image (will have the same physical space as the
                fixedVolume).
        outputVolume: (an existing file name)
                Required: output resampled moving image (will have the same physical space as the
                fixedVolume).

.. _nipype.interfaces.slicer.registration.BRAINSFit:


.. index:: BRAINSFit

BRAINSFit
---------

Code: http://github.com/nipy/nipype/blob/master/nipype/interfaces/slicer/registration.py#L206

Wraps command ** BRAINSFit **

title: General Registration (BRAINS)

category: Registration

description: Register a three-dimensional volume to a reference volume (Mattes Mutual Information by default). Full documentation avalable here: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.0/Modules/BRAINSFit. Method described in BRAINSFit: Mutual Information Registrations of Whole-Brain 3D Images, Using the Insight Toolkit, Johnson H.J., Harris G., Williams K., The Insight Journal, 2007. http://hdl.handle.net/1926/1291

version: 3.0.0

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Modules:BRAINSFit

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); Gregory Harris(1), Vincent Magnotta(1,2,3);  Andriy Fedorov(5) 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]
        NEVER_USE_THIS_FLAG_IT_IS_OUTDATED_00: (a boolean)
                DO NOT USE THIS FLAG
        NEVER_USE_THIS_FLAG_IT_IS_OUTDATED_01: (a boolean)
                DO NOT USE THIS FLAG
        NEVER_USE_THIS_FLAG_IT_IS_OUTDATED_02: (a boolean)
                DO NOT USE THIS FLAG
        ROIAutoClosingSize: (a float)
                This flag is only relavent when using ROIAUTO mode for initializing masks.  It defines
                the hole closing size in mm.  It is rounded up to the nearest whole pixel size in each
                direction. The default is to use a closing size of 9mm.  For mouse data this value may
                need to be reset to 0.9 or smaller.
        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.
        args: (a string)
                Additional parameters to the command
        backgroundFillValue: (a float)
                Background fill value for output image.
        bsplineTransform: (a boolean or a file name)
                (optional) Filename to which save the estimated transform. NOTE: You must set at least
                one output object (either a deformed image or a transform.  NOTE: USE THIS ONLY IF THE
                FINAL TRANSFORM IS BSpline
        costFunctionConvergenceFactor: (a float)
                 From itkLBFGSBOptimizer.h: Set/Get the CostFunctionConvergenceFactor. Algorithm
                terminates when the reduction in cost function is less than (factor * epsmcj) where
                epsmch is the machine precision. Typical values for factor: 1e+12 for low accuracy; 1e+7
                for moderate accuracy and 1e+1 for extremely high accuracy.  1e+9 seems to work well.,
        costMetric: ('MMI' or 'MSE' or 'NC' or 'MC')
                The cost metric to be used during fitting. Defaults to MMI. Options are MMI (Mattes
                Mutual Information), MSE (Mean Square Error), NC (Normalized Correlation), MC (Match
                Cardinality for binary images)
        debugLevel: (an integer)
                Display debug messages, and produce debug intermediate results.  0=OFF, 1=Minimal,
                10=Maximum debugging.
        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
        failureExitCode: (an integer)
                If the fit fails, exit with this status code.  (It can be used to force a successfult
                exit status of (0) if the registration fails due to reaching the maximum number of
                iterations.
        fixedBinaryVolume: (an existing file name)
                Fixed Image binary mask volume, ONLY FOR MANUAL ROI mode.
        fixedVolume: (an existing file name)
                The fixed image for registration by mutual information optimization.
        fixedVolumeTimeIndex: (an integer)
                The index in the time series for the 3D fixed image to fit, if 4-dimensional.
        forceMINumberOfThreads: (an integer)
                Force the the maximum number of threads to use for non thread safe MI metric.
        gui: (a boolean)
                Display intermediate image volumes for debugging.  NOTE:  This is not part of the
                standard build sytem, and probably does nothing on your installation.
        histogramMatch: (a boolean)
                Histogram Match the input images.  This is suitable for images of the same modality that
                may have different absolute scales, but the same overall intensity profile. Do NOT use
                if registering images from different modailties.
        ignore_exception: (a boolean, nipype default value: False)
                Print an error message instead of throwing an exception in case the interface fails to
                run
        initialTransform: (an existing file name)
                Filename of transform used to initialize the registration.  This CAN NOT be used with
                either CenterOfHeadLAlign, MomentsAlign, GeometryAlign, or initialTransform file.
        initializeTransformMode: ('Off' or 'useMomentsAlign' or 'useCenterOfHeadAlign' or
                 'useGeometryAlign' or 'useCenterOfROIAlign')
                Determine how to initialize the transform center.  GeometryAlign on assumes that the
                center of the voxel lattice of the images represent similar structures.  MomentsAlign
                assumes that the center of mass of the images represent similar structures.
                useCenterOfHeadAlign attempts to use the top of head and shape of neck to drive a center
                of mass estimate.  Off assumes that the physical space of the images are close, and that
                centering in terms of the image Origins is a good starting point.  This flag is mutually
                exclusive with the initialTransform flag.
        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, 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.
        linearTransform: (a boolean or a file name)
                (optional) Filename to which save the estimated transform. NOTE: You must set at least
                one output object (either a deformed image or a transform.  NOTE: USE THIS ONLY IF THE
                FINAL TRANSFORM IS ---NOT--- BSpline
        maskInferiorCutOffFromCenter: (a float)
                For use with --useCenterOfHeadAlign (and --maskProcessingMode ROIAUTO): the cut-off
                below the image centers, in millimeters,
        maskProcessingMode: ('NOMASK' or 'ROIAUTO' or 'ROI')
                What mode to use for using the masks.  If ROIAUTO is choosen, then the mask is
                implicitly defined using a otsu forground and hole filling algorithm. The Region Of
                Interest mode (choose ROI) uses the masks to define what parts of the image should be
                used for computing the transform.
        maxBSplineDisplacement: (a float)
                 Sets the maximum allowed displacements in image physical coordinates for BSpline
                control grid along each axis.  A value of 0.0 indicates that the problem should be
                unbounded.  NOTE:  This only constrains the BSpline portion, and does not limit the
                displacement from the associated bulk transform.  This can lead to a substantial
                reduction in computation time in the BSpline optimizer.,
        maximumStepLength: (a float)
                Internal debugging parameter, and should probably never be used from the command line.
                This will be removed in the future.
        medianFilterSize: (an integer)
                The radius for the optional MedianImageFilter preprocessing in all 3 directions.
        minimumStepLength: (a float)
                Each step in the optimization takes steps at least this big.  When none are possible,
                registration is complete.
        movingBinaryVolume: (an existing file name)
                Moving Image binary mask volume, ONLY FOR MANUAL ROI mode.
        movingVolume: (an existing file name)
                The moving image for registration by mutual information optimization.
        movingVolumeTimeIndex: (an integer)
                The index in the time series for the 3D moving image to fit, if 4-dimensional.
        numberOfHistogramBins: (an integer)
                The number of histogram levels
        numberOfIterations: (an integer)
                The maximum number of iterations to try before failing to converge.  Use an explicit
                limit like 500 or 1000 to manage risk of divergence
        numberOfMatchPoints: (an integer)
                the number of match points
        numberOfSamples: (an integer)
                The number of voxels sampled for mutual information computation.  Increase this for a
                slower, more careful fit.  You can also limit the sampling focus with ROI masks and
                ROIAUTO mask generation.
        numberOfThreads: (an integer)
                Explicitly specify the maximum number of threads to use. (default is auto-detected)
        outputFixedVolumeROI: (a boolean or a file name)
                The ROI automatically found in fixed image, ONLY FOR ROIAUTO mode.
        outputMovingVolumeROI: (a boolean or a file name)
                The ROI automatically found in moving image, ONLY FOR ROIAUTO mode.
        outputTransform: (a boolean or a file name)
                (optional) Filename to which save the (optional) estimated transform. NOTE: You must
                select either the outputTransform or the outputVolume option.
        outputVolume: (a boolean or a file name)
                (optional) Output image for registration. NOTE: You must select either the
                outputTransform or the outputVolume option.
        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.
        permitParameterVariation: (an integer)
                A bit vector to permit linear transform parameters to vary under optimization.  The
                vector order corresponds with transform parameters, and beyond the end ones fill in as a
                default.  For instance, you can choose to rotate only in x (pitch) with 1,0,0;  this is
                mostly for expert use in turning on and off individual degrees of freedom in rotation,
                translation or scaling without multiplying the number of transform representations; this
                trick is probably meaningless when tried with the general affine transform.
        projectedGradientTolerance: (a float)
                 From itkLBFGSBOptimizer.h: Set/Get the ProjectedGradientTolerance. Algorithm terminates
                when the project gradient is below the tolerance. Default lbfgsb value is 1e-5, but 1e-4
                seems to work well.,
        promptUser: (a boolean)
                Prompt the user to hit enter each time an image is sent to the DebugImageViewer
        relaxationFactor: (a float)
                Internal debugging parameter, and should probably never be used from the command line.
                This will be removed in the future.
        removeIntensityOutliers: (a float)
                The half percentage to decide outliers of image intensities. The default value is zero,
                which means no outlier removal. If the value of 0.005 is given, the moduel will throw
                away 0.005 % of both tails, so 0.01% of intensities in total would be ignored in its
                statistic calculation.
        reproportionScale: (a float)
                ScaleVersor3D 'Scale' compensation factor.  Increase this to put more rescaling in a
                ScaleVersor3D or ScaleSkewVersor3D search pattern.  1.0 works well with a
                translationScale of 1000.0
        scaleOutputValues: (a boolean)
                If true, and the voxel values do not fit within the minimum and maximum values of the
                desired outputVolumePixelType, then linearly scale the min/max output image voxel values
                to fit within the min/max range of the outputVolumePixelType.
        skewScale: (a float)
                ScaleSkewVersor3D Skew compensation factor.  Increase this to put more skew in a
                ScaleSkewVersor3D search pattern.  1.0 works well with a translationScale of 1000.0
        splineGridSize: (an integer)
                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.
        strippedOutputTransform: (a boolean or a file name)
                File name for the rigid component of the estimated affine transform. Can be used to
                rigidly register the moving image to the fixed image. NOTE:  This value is overwritten
                if either bsplineTransform or linearTransform is set.
        transformType: (a string)
                Specifies a list of registration types to be used.  The valid types are, Rigid,
                ScaleVersor3D, ScaleSkewVersor3D, Affine, and BSpline.  Specifiying more than one in a
                comma separated list will initialize the next stage with the previous results. If
                registrationClass flag is used, it overrides this parameter setting.
        translationScale: (a float)
                How much to scale up changes in position compared to unit rotational changes in radians
                -- decrease this to put more rotation in the search pattern.
        useAffine: (a boolean)
                Perform an Affine registration as part of the sequential registration steps.  This
                family of options superceeds the use of transformType if any of them are set.
        useBSpline: (a boolean)
                Perform a BSpline registration as part of the sequential registration steps.  This
                family of options superceeds the use of transformType if any of them are set.
        useCachingOfBSplineWeightsMode: ('ON' or 'OFF')
                This is a 5x speed advantage at the expense of requiring much more memory.  Only
                relevant when transformType is BSpline.
        useComposite: (a boolean)
                Perform a Composite registration as part of the sequential registration steps.  This
                family of options superceeds the use of transformType if any of them are set.
        useExplicitPDFDerivativesMode: ('AUTO' or 'ON' or 'OFF')
                Using mode AUTO means OFF for BSplineDeformableTransforms and ON for the linear
                transforms.  The ON alternative uses more memory to sometimes do a better job.
        useRigid: (a boolean)
                Perform a rigid registration as part of the sequential registration steps.  This family
                of options superceeds the use of transformType if any of them are set.
        useScaleSkewVersor3D: (a boolean)
                Perform a ScaleSkewVersor3D registration as part of the sequential registration steps.
                This family of options superceeds the use of transformType if any of them are set.
        useScaleVersor3D: (a boolean)
                Perform a ScaleVersor3D registration as part of the sequential registration steps.  This
                family of options superceeds the use of transformType if any of them are set.
        writeTransformOnFailure: (a boolean)
                Flag to save the final transform even if the numberOfIterations are reached without
                convergence. (Intended for use when --failureExitCode 0 )

Outputs::

        bsplineTransform: (an existing file name)
                (optional) Filename to which save the estimated transform. NOTE: You must set at least
                one output object (either a deformed image or a transform.  NOTE: USE THIS ONLY IF THE
                FINAL TRANSFORM IS BSpline
        linearTransform: (an existing file name)
                (optional) Filename to which save the estimated transform. NOTE: You must set at least
                one output object (either a deformed image or a transform.  NOTE: USE THIS ONLY IF THE
                FINAL TRANSFORM IS ---NOT--- BSpline
        outputFixedVolumeROI: (an existing file name)
                The ROI automatically found in fixed image, ONLY FOR ROIAUTO mode.
        outputMovingVolumeROI: (an existing file name)
                The ROI automatically found in moving image, ONLY FOR ROIAUTO mode.
        outputTransform: (an existing file name)
                (optional) Filename to which save the (optional) estimated transform. NOTE: You must
                select either the outputTransform or the outputVolume option.
        outputVolume: (an existing file name)
                (optional) Output image for registration. NOTE: You must select either the
                outputTransform or the outputVolume option.
        strippedOutputTransform: (an existing file name)
                File name for the rigid component of the estimated affine transform. Can be used to
                rigidly register the moving image to the fixed image. NOTE:  This value is overwritten
                if either bsplineTransform or linearTransform is set.

.. _nipype.interfaces.slicer.registration.BRAINSResample:


.. index:: BRAINSResample

BRAINSResample
--------------

Code: http://github.com/nipy/nipype/blob/master/nipype/interfaces/slicer/registration.py#L27

Wraps command ** BRAINSResample **

title: Resample Image (BRAINS)

category: Registration

description:
          This program collects together three common image processing tasks that all involve resampling an image volume: Resampling to a new resolution and spacing, applying a transformation (using an ITK transform IO mechanisms) and Warping (using a vector image deformation field).  Full documentation available here: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.0/Modules/BRAINSResample.


version: 3.0.0

documentation-url: http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSResample

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

contributor: This tool was developed by Vincent Magnotta, Greg Harris, and Hans Johnson.

acknowledgements: The development of this tool was supported by funding from grants NS050568 and NS40068 from the National Institute of Neurological Disorders and Stroke and grants MH31593, MH40856, from the National Institute of Mental Health.

Inputs::

        [Mandatory]

        [Optional]
        args: (a string)
                Additional parameters to the command
        defaultValue: (a float)
                Default voxel value
        deformationVolume: (an existing file name)
                Displacement Field to be used to warp the image
        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
        gridSpacing: (an integer)
                Add warped grid to output image to help show the deformation that occured with specified
                spacing.   A spacing of 0 in a dimension indicates that grid lines should be rendered to
                fall exactly (i.e. do not allow displacements off that plane).  This is useful for
                makeing a 2D image of grid lines from the 3D space
        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)
                Image To Warp
        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
        inverseTransform: (a boolean)
                True/False is to compute inverse of given transformation. Default is false
        numberOfThreads: (an integer)
                Explicitly specify the maximum number of threads to use.
        outputVolume: (a boolean or a file name)
                Resulting deformed image
        pixelType: ('float' or 'short' or 'ushort' or 'int' or 'uint' or 'uchar' or 'binary')
                Specifies the pixel type for the input/output images.  The "binary" pixel type uses a
                modified algorithm whereby the image is read in as unsigned char, a signed distance map
                is created, signed distance map is resampled, and then a thresholded image of type
                unsigned char is written to disk.
        referenceVolume: (an existing file name)
                Reference image used only to define the output space. If not specified, the warping is
                done in the same space as the image to warp.
        warpTransform: (an existing file name)
                Filename for the BRAINSFit transform used in place of the deformation field

Outputs::

        outputVolume: (an existing file name)
                Resulting deformed image

.. _nipype.interfaces.slicer.registration.VBRAINSDemonWarp:


.. index:: VBRAINSDemonWarp

VBRAINSDemonWarp
----------------

Code: http://github.com/nipy/nipype/blob/master/nipype/interfaces/slicer/registration.py#L104

Wraps command ** VBRAINSDemonWarp **

title: Vector Demon Registration (BRAINS)

category: Registration

description:
    This program finds a deformation field to warp a moving image onto a fixed image.  The images must be of the same signal kind, and contain an image of the same kind of object.  This program uses the Thirion Demons warp software in ITK, the Insight Toolkit.  Additional information is available at: http://www.nitrc.org/projects/brainsdemonwarp.



version: 3.0.0

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Modules:BRAINSDemonWarp

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

contributor: This tool was developed by Hans J. Johnson and Greg Harris.

acknowledgements: The development of this tool was supported by funding from grants NS050568 and NS40068 from the National Institute of Neurological Disorders and Stroke and grants MH31593, MH40856, from the National Institute of Mental Health.

Inputs::

        [Mandatory]

        [Optional]
        args: (a string)
                Additional parameters to the command
        arrayOfPyramidLevelIterations: (an integer)
                The number of iterations for each pyramid level
        backgroundFillValue: (an integer)
                Replacement value to overwrite background when performing BOBF
        checkerboardPatternSubdivisions: (an integer)
                Number of Checkerboard subdivisions in all 3 directions
        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
        fixedBinaryVolume: (an existing file name)
                Mask filename for desired region of interest in the Fixed image.
        fixedVolume: (an existing file name)
                Required: input fixed (target) image
        gradient_type: ('0' or '1' or '2')
                Type of gradient used for computing the demons force (0 is symmetrized, 1 is fixed
                image, 2 is moving image)
        gui: (a boolean)
                Display intermediate image volumes for debugging
        histogramMatch: (a boolean)
                Histogram Match the input images.  This is suitable for images of the same modality that
                may have different absolute scales, but the same overall intensity profile.
        ignore_exception: (a boolean, nipype default value: False)
                Print an error message instead of throwing an exception in case the interface fails to
                run
        initializeWithDeformationField: (an existing file name)
                Initial deformation field vector image file name
        initializeWithTransform: (an existing file name)
                Initial Transform filename
        inputPixelType: ('float' or 'short' or 'ushort' or 'int' or 'uchar')
                Input volumes will be typecast to this format: float|short|ushort|int|uchar
        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
        lowerThresholdForBOBF: (an integer)
                Lower threshold for performing BOBF
        makeBOBF: (a boolean)
                Flag to make Brain-Only Background-Filled versions of the input and target volumes.
        max_step_length: (a float)
                Maximum length of an update vector (0: no restriction)
        medianFilterSize: (an integer)
                Median filter radius in all 3 directions.  When images have a lot of salt and pepper
                noise, this step can improve the registration.
        minimumFixedPyramid: (an integer)
                The shrink factor for the first level of the fixed image pyramid. (i.e. start at 1/16
                scale, then 1/8, then 1/4, then 1/2, and finally full scale)
        minimumMovingPyramid: (an integer)
                The shrink factor for the first level of the moving image pyramid. (i.e. start at 1/16
                scale, then 1/8, then 1/4, then 1/2, and finally full scale)
        movingBinaryVolume: (an existing file name)
                Mask filename for desired region of interest in the Moving image.
        movingVolume: (an existing file name)
                Required: input moving image
        neighborhoodForBOBF: (an integer)
                neighborhood in all 3 directions to be included when performing BOBF
        numberOfBCHApproximationTerms: (an integer)
                Number of terms in the BCH expansion
        numberOfHistogramBins: (an integer)
                The number of histogram levels
        numberOfMatchPoints: (an integer)
                The number of match points for histrogramMatch
        numberOfPyramidLevels: (an integer)
                Number of image pyramid levels to use in the multi-resolution registration.
        numberOfThreads: (an integer)
                Explicitly specify the maximum number of threads to use.
        outputCheckerboardVolume: (a boolean or a file name)
                Genete a checkerboard image volume between the fixedVolume and the deformed
                movingVolume.
        outputDebug: (a boolean)
                Flag to write debugging images after each step.
        outputDeformationFieldVolume: (a boolean or a file name)
                Output deformation field vector image (will have the same physical space as the
                fixedVolume).
        outputDisplacementFieldPrefix: (a string)
                Displacement field filename prefix for writing separate x, y, and z component images
        outputNormalized: (a boolean)
                Flag to warp and write the normalized images to output.  In normalized images the image
                values are fit-scaled to be between 0 and the maximum storage type value.
        outputPixelType: ('float' or 'short' or 'ushort' or 'int' or 'uchar')
                outputVolume will be typecast to this format: float|short|ushort|int|uchar
        outputVolume: (a boolean or a file name)
                Required: output resampled moving image (will have the same physical space as the
                fixedVolume).
        promptUser: (a boolean)
                Prompt the user to hit enter each time an image is sent to the DebugImageViewer
        registrationFilterType: ('Demons' or 'FastSymmetricForces' or 'Diffeomorphic' or
                 'LogDemons' or 'SymmetricLogDemons')
                Registration Filter Type:
                Demons|FastSymmetricForces|Diffeomorphic|LogDemons|SymmetricLogDemons
        seedForBOBF: (an integer)
                coordinates in all 3 directions for Seed when performing BOBF
        smoothDeformationFieldSigma: (a float)
                A gaussian smoothing value to be applied to the deformation feild at each iteration.
        upFieldSmoothing: (a float)
                Smoothing sigma for the update field at each iteration
        upperThresholdForBOBF: (an integer)
                Upper threshold for performing BOBF
        use_vanilla_dem: (a boolean)
                Run vanilla demons algorithm
        weightFactors: (a float)
                Weight fatctors for each input images

Outputs::

        outputCheckerboardVolume: (an existing file name)
                Genete a checkerboard image volume between the fixedVolume and the deformed
                movingVolume.
        outputDeformationFieldVolume: (an existing file name)
                Output deformation field vector image (will have the same physical space as the
                fixedVolume).
        outputVolume: (an existing file name)
                Required: output resampled moving image (will have the same physical space as the
                fixedVolume).
