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# interfaces.slicer.legacy.registration

## AffineRegistration

Link to code

Wraps command **AffineRegistration **

title: Affine Registration

category: Legacy.Registration

description: Registers two images together using an affine transform and mutual information. This module is often used to align images of different subjects or images of the same subject from different modalities.

This module can smooth images prior to registration to mitigate noise and improve convergence. Many of the registration parameters require a working knowledge of the algorithm although the default parameters are sufficient for many registration tasks.

version: 0.1.0.$Revision: 19608 $(alpha)

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/AffineRegistration

contributor: Daniel Blezek (GE)

acknowledgements: This module was developed by Daniel Blezek while at GE Research with contributions from Jim Miller.

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.

Inputs:

    [Mandatory]

    [Optional]
    FixedImageFileName: (an existing file name)
            Fixed image to which to register
            flag: %s, position: -2
    MovingImageFileName: (an existing file name)
            Moving image
            flag: %s, position: -1
    args: (a string)
            Additional parameters to the command
            flag: %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
    fixedsmoothingfactor: (an integer)
            Amount of smoothing applied to fixed image prior to registration.
            Default is 0 (none). Range is 0-5 (unitless). Consider smoothing the
            input data if there is considerable amounts of noise or the noise
            pattern in the fixed and moving images is very different.
            flag: --fixedsmoothingfactor %d
    histogrambins: (an integer)
            Number of histogram bins to use for Mattes Mutual Information.
            Reduce the number of bins if a registration fails. If the number of
            bins is too large, the estimated PDFs will be a field of impulses
            and will inhibit reliable registration estimation.
            flag: --histogrambins %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
    initialtransform: (an existing file name)
            Initial transform for aligning the fixed and moving image. Maps
            positions in the fixed coordinate frame to positions in the moving
            coordinate frame. Optional.
            flag: --initialtransform %s
    iterations: (an integer)
            Number of iterations
            flag: --iterations %d
    movingsmoothingfactor: (an integer)
            Amount of smoothing applied to moving image prior to registration.
            Default is 0 (none). Range is 0-5 (unitless). Consider smoothing the
            input data if there is considerable amounts of noise or the noise
            pattern in the fixed and moving images is very different.
            flag: --movingsmoothingfactor %d
    outputtransform: (a boolean or a file name)
            Transform calculated that aligns the fixed and moving image. Maps
            positions in the fixed coordinate frame to the moving coordinate
            frame. Optional (specify an output transform or an output volume or
            both).
            flag: --outputtransform %s
    resampledmovingfilename: (a boolean or a file name)
            Resampled moving image to the fixed image coordinate frame. Optional
            (specify an output transform or an output volume or both).
            flag: --resampledmovingfilename %s
    spatialsamples: (an integer)
            Number of spatial samples to use in estimating Mattes Mutual
            Information. Larger values yield more accurate PDFs and improved
            registration quality.
            flag: --spatialsamples %d
    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
    translationscale: (a float)
            Relative scale of translations to rotations, i.e. a value of 100
            means 10mm = 1 degree. (Actual scale used is
            1/(TranslationScale^2)). This parameter is used to 'weight' or
            'standardized' the transform parameters and their effect on the
            registration objective function.
            flag: --translationscale %f

Outputs:

    outputtransform: (an existing file name)
            Transform calculated that aligns the fixed and moving image. Maps
            positions in the fixed coordinate frame to the moving coordinate
            frame. Optional (specify an output transform or an output volume or
            both).
    resampledmovingfilename: (an existing file name)
            Resampled moving image to the fixed image coordinate frame. Optional
            (specify an output transform or an output volume or both).

## BSplineDeformableRegistration

Link to code

Wraps command **BSplineDeformableRegistration **

title: BSpline Deformable Registration

category: Legacy.Registration

description: Registers two images together using BSpline transform and mutual information.

version: 0.1.0.$Revision: 19608 $(alpha)

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BSplineDeformableRegistration

contributor: Bill Lorensen (GE)

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.

Inputs:

    [Mandatory]

    [Optional]
    FixedImageFileName: (an existing file name)
            Fixed image to which to register
            flag: %s, position: -2
    MovingImageFileName: (an existing file name)
            Moving image
            flag: %s, position: -1
    args: (a string)
            Additional parameters to the command
            flag: %s
    constrain: (a boolean)
            Constrain the deformation to the amount specified in Maximum
            Deformation
            flag: --constrain
    default: (an integer)
            Default pixel value used if resampling a pixel outside of the
            volume.
            flag: --default %d
    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
    gridSize: (an integer)
            Number of grid points on interior of the fixed image. Larger grid
            sizes allow for finer registrations.
            flag: --gridSize %d
    histogrambins: (an integer)
            Number of histogram bins to use for Mattes Mutual Information.
            Reduce the number of bins if a deformable registration fails. If the
            number of bins is too large, the estimated PDFs will be a field of
            impulses and will inhibit reliable registration estimation.
            flag: --histogrambins %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
    initialtransform: (an existing file name)
            Initial transform for aligning the fixed and moving image. Maps
            positions in the fixed coordinate frame to positions in the moving
            coordinate frame. This transform should be an affine or rigid
            transform. It is used an a bulk transform for the BSpline. Optional.
            flag: --initialtransform %s
    iterations: (an integer)
            Number of iterations
            flag: --iterations %d
    maximumDeformation: (a float)
            If Constrain Deformation is checked, limit the deformation to this
            amount.
            flag: --maximumDeformation %f
    outputtransform: (a boolean or a file name)
            Transform calculated that aligns the fixed and moving image. Maps
            positions from the fixed coordinate frame to the moving coordinate
            frame. Optional (specify an output transform or an output volume or
            both).
            flag: --outputtransform %s
    outputwarp: (a boolean or a file name)
            Vector field that applies an equivalent warp as the BSpline. Maps
            positions from the fixed coordinate frame to the moving coordinate
            frame. Optional.
            flag: --outputwarp %s
    resampledmovingfilename: (a boolean or a file name)
            Resampled moving image to fixed image coordinate frame. Optional
            (specify an output transform or an output volume or both).
            flag: --resampledmovingfilename %s
    spatialsamples: (an integer)
            Number of spatial samples to use in estimating Mattes Mutual
            Information. Larger values yield more accurate PDFs and improved
            registration quality.
            flag: --spatialsamples %d
    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

Outputs:

    outputtransform: (an existing file name)
            Transform calculated that aligns the fixed and moving image. Maps
            positions from the fixed coordinate frame to the moving coordinate
            frame. Optional (specify an output transform or an output volume or
            both).
    outputwarp: (an existing file name)
            Vector field that applies an equivalent warp as the BSpline. Maps
            positions from the fixed coordinate frame to the moving coordinate
            frame. Optional.
    resampledmovingfilename: (an existing file name)
            Resampled moving image to fixed image coordinate frame. Optional
            (specify an output transform or an output volume or both).

## ExpertAutomatedRegistration

Link to code

Wraps command **ExpertAutomatedRegistration **

title: Expert Automated Registration

category: Legacy.Registration

description: Provides rigid, affine, and BSpline registration methods via a simple GUI

version: 0.1.0.$Revision: 2104 $(alpha)

documentation-url: http://www.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/ExpertAutomatedRegistration

contributor: Stephen R Aylward (Kitware), Casey B Goodlett (Kitware)

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.

Inputs:

    [Mandatory]

    [Optional]
    affineMaxIterations: (an integer)
            Maximum number of affine optimization iterations
            flag: --affineMaxIterations %d
    affineSamplingRatio: (a float)
            Portion of the image to use in computing the metric during affine
            registration
            flag: --affineSamplingRatio %f
    args: (a string)
            Additional parameters to the command
            flag: %s
    bsplineMaxIterations: (an integer)
            Maximum number of bspline optimization iterations
            flag: --bsplineMaxIterations %d
    bsplineSamplingRatio: (a float)
            Portion of the image to use in computing the metric during BSpline
            registration
            flag: --bsplineSamplingRatio %f
    controlPointSpacing: (an integer)
            Number of pixels between control points
            flag: --controlPointSpacing %d
    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
    expectedOffset: (a float)
            Expected misalignment after initialization
            flag: --expectedOffset %f
    expectedRotation: (a float)
            Expected misalignment after initialization
            flag: --expectedRotation %f
    expectedScale: (a float)
            Expected misalignment after initialization
            flag: --expectedScale %f
    expectedSkew: (a float)
            Expected misalignment after initialization
            flag: --expectedSkew %f
    fixedImage: (an existing file name)
            Image which defines the space into which the moving image is
            registered
            flag: %s, position: -2
    fixedImageMask: (an existing file name)
            Image which defines a mask for the fixed image
            flag: --fixedImageMask %s
    fixedLandmarks: (a list of items which are a list of from 3 to 3
             items which are a float)
            Ordered list of landmarks in the fixed image
            flag: --fixedLandmarks %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
    initialization: ('None' or 'Landmarks' or 'ImageCenters' or
             'CentersOfMass' or 'SecondMoments')
            Method to prime the registration process
            flag: --initialization %s
    interpolation: ('NearestNeighbor' or 'Linear' or 'BSpline')
            Method for interpolation within the optimization process
            flag: --interpolation %s
    loadTransform: (an existing file name)
            Load a transform that is immediately applied to the moving image
            flag: --loadTransform %s
    metric: ('MattesMI' or 'NormCorr' or 'MeanSqrd')
            Method to quantify image match
            flag: --metric %s
    minimizeMemory: (a boolean)
            Reduce the amount of memory required at the cost of increased
            computation time
            flag: --minimizeMemory
    movingImage: (an existing file name)
            The transform goes from the fixed image's space into the moving
            image's space
            flag: %s, position: -1
    movingLandmarks: (a list of items which are a list of from 3 to 3
             items which are a float)
            Ordered list of landmarks in the moving image
            flag: --movingLandmarks %s...
    numberOfThreads: (an integer)
            Number of CPU threads to use
            flag: --numberOfThreads %d
    randomNumberSeed: (an integer)
            Seed to generate a consistent random number sequence
            flag: --randomNumberSeed %d
    registration: ('None' or 'Initial' or 'Rigid' or 'Affine' or
             'BSpline' or 'PipelineRigid' or 'PipelineAffine' or
             'PipelineBSpline')
            Method for the registration process
            flag: --registration %s
    resampledImage: (a boolean or a file name)
            Registration results
            flag: --resampledImage %s
    rigidMaxIterations: (an integer)
            Maximum number of rigid optimization iterations
            flag: --rigidMaxIterations %d
    rigidSamplingRatio: (a float)
            Portion of the image to use in computing the metric during rigid
            registration
            flag: --rigidSamplingRatio %f
    sampleFromOverlap: (a boolean)
            Limit metric evaluation to the fixed image region overlapped by the
            moving image
            flag: --sampleFromOverlap
    saveTransform: (a boolean or a file name)
            Save the transform that results from registration
            flag: --saveTransform %s
    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
    verbosityLevel: ('Silent' or 'Standard' or 'Verbose')
            Level of detail of reporting progress
            flag: --verbosityLevel %s

Outputs:

    resampledImage: (an existing file name)
            Registration results
    saveTransform: (an existing file name)
            Save the transform that results from registration

## LinearRegistration

Link to code

Wraps command **LinearRegistration **

title: Linear Registration

category: Legacy.Registration

description: Registers two images together using a rigid transform and mutual information.

version: 0.1.0.$Revision: 19608 $(alpha)

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/LinearRegistration

contributor: Daniel Blezek (GE)

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.

Inputs:

    [Mandatory]

    [Optional]
    FixedImageFileName: (an existing file name)
            Fixed image to which to register
            flag: %s, position: -2
    MovingImageFileName: (an existing file name)
            Moving image
            flag: %s, position: -1
    args: (a string)
            Additional parameters to the command
            flag: %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
    fixedsmoothingfactor: (an integer)
            Amount of smoothing applied to fixed image prior to registration.
            Default is 0 (none). Range is 0-5 (unitless). Consider smoothing the
            input data if there is considerable amounts of noise or the noise
            pattern in the fixed and moving images is very different.
            flag: --fixedsmoothingfactor %d
    histogrambins: (an integer)
            Number of histogram bins to use for Mattes Mutual Information.
            Reduce the number of bins if a registration fails. If the number of
            bins is too large, the estimated PDFs will be a field of impulses
            and will inhibit reliable registration estimation.
            flag: --histogrambins %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
    initialtransform: (an existing file name)
            Initial transform for aligning the fixed and moving image. Maps
            positions in the fixed coordinate frame to positions in the moving
            coordinate frame. Optional.
            flag: --initialtransform %s
    iterations: (a list of items which are an integer)
            Comma separated list of iterations. Must have the same number of
            elements as the learning rate.
            flag: --iterations %s
    learningrate: (a list of items which are a float)
            Comma separated list of learning rates. Learning rate is a scale
            factor on the gradient of the registration objective function
            (gradient with respect to the parameters of the transformation) used
            to update the parameters of the transformation during optimization.
            Smaller values cause the optimizer to take smaller steps through the
            parameter space. Larger values are typically used early in the
            registration process to take large jumps in parameter space followed
            by smaller values to home in on the optimum value of the
            registration objective function. Default is: 0.01, 0.005, 0.0005,
            0.0002. Must have the same number of elements as iterations.
            flag: --learningrate %s
    movingsmoothingfactor: (an integer)
            Amount of smoothing applied to moving image prior to registration.
            Default is 0 (none). Range is 0-5 (unitless). Consider smoothing the
            input data if there is considerable amounts of noise or the noise
            pattern in the fixed and moving images is very different.
            flag: --movingsmoothingfactor %d
    outputtransform: (a boolean or a file name)
            Transform calculated that aligns the fixed and moving image. Maps
            positions in the fixed coordinate frame to the moving coordinate
            frame. Optional (specify an output transform or an output volume or
            both).
            flag: --outputtransform %s
    resampledmovingfilename: (a boolean or a file name)
            Resampled moving image to the fixed image coordinate frame. Optional
            (specify an output transform or an output volume or both).
            flag: --resampledmovingfilename %s
    spatialsamples: (an integer)
            Number of spatial samples to use in estimating Mattes Mutual
            Information. Larger values yield more accurate PDFs and improved
            registration quality.
            flag: --spatialsamples %d
    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
    translationscale: (a float)
            Relative scale of translations to rotations, i.e. a value of 100
            means 10mm = 1 degree. (Actual scale used 1/(TranslationScale^2)).
            This parameter is used to 'weight' or 'standardized' the transform
            parameters and their effect on the registration objective function.
            flag: --translationscale %f

Outputs:

    outputtransform: (an existing file name)
            Transform calculated that aligns the fixed and moving image. Maps
            positions in the fixed coordinate frame to the moving coordinate
            frame. Optional (specify an output transform or an output volume or
            both).
    resampledmovingfilename: (an existing file name)
            Resampled moving image to the fixed image coordinate frame. Optional
            (specify an output transform or an output volume or both).

## MultiResolutionAffineRegistration

Link to code

Wraps command **MultiResolutionAffineRegistration **

title: Robust Multiresolution Affine Registration

category: Legacy.Registration

description: Provides affine registration using multiple resolution levels and decomposed affine transforms.

version: 0.1.0.$Revision: 2104 $(alpha)

documentation-url: http://www.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/MultiResolutionAffineRegistration

contributor: Casey B Goodlett (Utah)

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.

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %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
    fixedImage: (an existing file name)
            Image which defines the space into which the moving image is
            registered
            flag: %s, position: -2
    fixedImageMask: (an existing file name)
            Label image which defines a mask of interest for the fixed image
            flag: --fixedImageMask %s
    fixedImageROI: (a list of items which are any value)
            Label image which defines a ROI of interest for the fixed image
            flag: --fixedImageROI %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
    metricTolerance: (a float)
            flag: --metricTolerance %f
    movingImage: (an existing file name)
            The transform goes from the fixed image's space into the moving
            image's space
            flag: %s, position: -1
    numIterations: (an integer)
            Number of iterations to run at each resolution level.
            flag: --numIterations %d
    numLineIterations: (an integer)
            Number of iterations to run at each resolution level.
            flag: --numLineIterations %d
    resampledImage: (a boolean or a file name)
            Registration results
            flag: --resampledImage %s
    saveTransform: (a boolean or a file name)
            Save the output transform from the registration
            flag: --saveTransform %s
    stepSize: (a float)
            The maximum step size of the optimizer in voxels
            flag: --stepSize %f
    stepTolerance: (a float)
            The maximum step size of the optimizer in voxels
            flag: --stepTolerance %f
    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

Outputs:

    resampledImage: (an existing file name)
            Registration results
    saveTransform: (an existing file name)
            Save the output transform from the registration

## RigidRegistration

Link to code

Wraps command **RigidRegistration **

title: Rigid Registration

category: Legacy.Registration

description: Registers two images together using a rigid transform and mutual information.

This module was originally distributed as “Linear registration” but has been renamed to eliminate confusion with the “Affine registration” module.

This module is often used to align images of different subjects or images of the same subject from different modalities.

This module can smooth images prior to registration to mitigate noise and improve convergence. Many of the registration parameters require a working knowledge of the algorithm although the default parameters are sufficient for many registration tasks.

version: 0.1.0.$Revision: 19608 $(alpha)

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/RigidRegistration

contributor: Daniel Blezek (GE)

acknowledgements: This module was developed by Daniel Blezek while at GE Research with contributions from Jim Miller.

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.

Inputs:

    [Mandatory]

    [Optional]
    FixedImageFileName: (an existing file name)
            Fixed image to which to register
            flag: %s, position: -2
    MovingImageFileName: (an existing file name)
            Moving image
            flag: %s, position: -1
    args: (a string)
            Additional parameters to the command
            flag: %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
    fixedsmoothingfactor: (an integer)
            Amount of smoothing applied to fixed image prior to registration.
            Default is 0 (none). Range is 0-5 (unitless). Consider smoothing the
            input data if there is considerable amounts of noise or the noise
            pattern in the fixed and moving images is very different.
            flag: --fixedsmoothingfactor %d
    histogrambins: (an integer)
            Number of histogram bins to use for Mattes Mutual Information.
            Reduce the number of bins if a registration fails. If the number of
            bins is too large, the estimated PDFs will be a field of impulses
            and will inhibit reliable registration estimation.
            flag: --histogrambins %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
    initialtransform: (an existing file name)
            Initial transform for aligning the fixed and moving image. Maps
            positions in the fixed coordinate frame to positions in the moving
            coordinate frame. Optional.
            flag: --initialtransform %s
    iterations: (a list of items which are an integer)
            Comma separated list of iterations. Must have the same number of
            elements as the learning rate.
            flag: --iterations %s
    learningrate: (a list of items which are a float)
            Comma separated list of learning rates. Learning rate is a scale
            factor on the gradient of the registration objective function
            (gradient with respect to the parameters of the transformation) used
            to update the parameters of the transformation during optimization.
            Smaller values cause the optimizer to take smaller steps through the
            parameter space. Larger values are typically used early in the
            registration process to take large jumps in parameter space followed
            by smaller values to home in on the optimum value of the
            registration objective function. Default is: 0.01, 0.005, 0.0005,
            0.0002. Must have the same number of elements as iterations.
            flag: --learningrate %s
    movingsmoothingfactor: (an integer)
            Amount of smoothing applied to moving image prior to registration.
            Default is 0 (none). Range is 0-5 (unitless). Consider smoothing the
            input data if there is considerable amounts of noise or the noise
            pattern in the fixed and moving images is very different.
            flag: --movingsmoothingfactor %d
    outputtransform: (a boolean or a file name)
            Transform calculated that aligns the fixed and moving image. Maps
            positions in the fixed coordinate frame to the moving coordinate
            frame. Optional (specify an output transform or an output volume or
            both).
            flag: --outputtransform %s
    resampledmovingfilename: (a boolean or a file name)
            Resampled moving image to the fixed image coordinate frame. Optional
            (specify an output transform or an output volume or both).
            flag: --resampledmovingfilename %s
    spatialsamples: (an integer)
            Number of spatial samples to use in estimating Mattes Mutual
            Information. Larger values yield more accurate PDFs and improved
            registration quality.
            flag: --spatialsamples %d
    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
    testingmode: (a boolean)
            Enable testing mode. Input transform will be used to construct
            floating image. The floating image will be ignored if passed.
            flag: --testingmode
    translationscale: (a float)
            Relative scale of translations to rotations, i.e. a value of 100
            means 10mm = 1 degree. (Actual scale used 1/(TranslationScale^2)).
            This parameter is used to 'weight' or 'standardized' the transform
            parameters and their effect on the registration objective function.
            flag: --translationscale %f

Outputs:

    outputtransform: (an existing file name)
            Transform calculated that aligns the fixed and moving image. Maps
            positions in the fixed coordinate frame to the moving coordinate
            frame. Optional (specify an output transform or an output volume or
            both).
    resampledmovingfilename: (an existing file name)
            Resampled moving image to the fixed image coordinate frame. Optional
            (specify an output transform or an output volume or both).