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

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


.. _nipype.interfaces.slicer.legacy.registration.AffineRegistration:


.. index:: AffineRegistration

AffineRegistration
------------------

`Link to code <http://github.com/nipy/nipype/tree/e63e055194d62d2bdc4665688261c03a42fd0025/nipype/interfaces/slicer/legacy/registration.py#L73>`__

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]
        terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
                Control terminal output: `stream` - displays to terminal
                immediately, `allatonce` - waits till command is finished to display
                output, `file` - writes output to file, `none` - output is ignored

        [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
        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).

.. _nipype.interfaces.slicer.legacy.registration.BSplineDeformableRegistration:


.. index:: BSplineDeformableRegistration

BSplineDeformableRegistration
-----------------------------

`Link to code <http://github.com/nipy/nipype/tree/e63e055194d62d2bdc4665688261c03a42fd0025/nipype/interfaces/slicer/legacy/registration.py#L31>`__

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]
        terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
                Control terminal output: `stream` - displays to terminal
                immediately, `allatonce` - waits till command is finished to display
                output, `file` - writes output to file, `none` - output is ignored

        [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

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).

.. _nipype.interfaces.slicer.legacy.registration.ExpertAutomatedRegistration:


.. index:: ExpertAutomatedRegistration

ExpertAutomatedRegistration
---------------------------

`Link to code <http://github.com/nipy/nipype/tree/e63e055194d62d2bdc4665688261c03a42fd0025/nipype/interfaces/slicer/legacy/registration.py#L277>`__

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]
        terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
                Control terminal output: `stream` - displays to terminal
                immediately, `allatonce` - waits till command is finished to display
                output, `file` - writes output to file, `none` - output is ignored

        [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 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 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
        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

.. _nipype.interfaces.slicer.legacy.registration.LinearRegistration:


.. index:: LinearRegistration

LinearRegistration
------------------

`Link to code <http://github.com/nipy/nipype/tree/e63e055194d62d2bdc4665688261c03a42fd0025/nipype/interfaces/slicer/legacy/registration.py#L218>`__

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]
        terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
                Control terminal output: `stream` - displays to terminal
                immediately, `allatonce` - waits till command is finished to display
                output, `file` - writes output to file, `none` - output is ignored

        [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)
                Comma separated list of iterations. Must have the same number of
                elements as the learning rate.
                flag: --iterations %s
        learningrate: (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
        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).

.. _nipype.interfaces.slicer.legacy.registration.MultiResolutionAffineRegistration:


.. index:: MultiResolutionAffineRegistration

MultiResolutionAffineRegistration
---------------------------------

`Link to code <http://github.com/nipy/nipype/tree/e63e055194d62d2bdc4665688261c03a42fd0025/nipype/interfaces/slicer/legacy/registration.py#L121>`__

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]
        terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
                Control terminal output: `stream` - displays to terminal
                immediately, `allatonce` - waits till command is finished to display
                output, `file` - writes output to file, `none` - output is ignored

        [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

Outputs::

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

.. _nipype.interfaces.slicer.legacy.registration.RigidRegistration:


.. index:: RigidRegistration

RigidRegistration
-----------------

`Link to code <http://github.com/nipy/nipype/tree/e63e055194d62d2bdc4665688261c03a42fd0025/nipype/interfaces/slicer/legacy/registration.py#L165>`__

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]
        terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
                Control terminal output: `stream` - displays to terminal
                immediately, `allatonce` - waits till command is finished to display
                output, `file` - writes output to file, `none` - output is ignored

        [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)
                Comma separated list of iterations. Must have the same number of
                elements as the learning rate.
                flag: --iterations %s
        learningrate: (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
        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).
