interfaces.slicer.legacy.registration¶
AffineRegistration¶
Wraps the executable 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:
[Optional]
fixedsmoothingfactor: (an integer (int or long))
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.
argument: ``--fixedsmoothingfactor %d``
movingsmoothingfactor: (an integer (int or long))
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.
argument: ``--movingsmoothingfactor %d``
histogrambins: (an integer (int or long))
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.
argument: ``--histogrambins %d``
spatialsamples: (an integer (int or long))
Number of spatial samples to use in estimating Mattes Mutual
Information. Larger values yield more accurate PDFs and improved
registration quality.
argument: ``--spatialsamples %d``
iterations: (an integer (int or long))
Number of iterations
argument: ``--iterations %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.
argument: ``--translationscale %f``
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.
argument: ``--initialtransform %s``
FixedImageFileName: (an existing file name)
Fixed image to which to register
argument: ``%s``, position: -2
MovingImageFileName: (an existing file name)
Moving image
argument: ``%s``, position: -1
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).
argument: ``--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).
argument: ``--resampledmovingfilename %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
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¶
Wraps the executable 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:
[Optional]
iterations: (an integer (int or long))
Number of iterations
argument: ``--iterations %d``
gridSize: (an integer (int or long))
Number of grid points on interior of the fixed image. Larger grid
sizes allow for finer registrations.
argument: ``--gridSize %d``
histogrambins: (an integer (int or long))
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.
argument: ``--histogrambins %d``
spatialsamples: (an integer (int or long))
Number of spatial samples to use in estimating Mattes Mutual
Information. Larger values yield more accurate PDFs and improved
registration quality.
argument: ``--spatialsamples %d``
constrain: (a boolean)
Constrain the deformation to the amount specified in Maximum
Deformation
argument: ``--constrain ``
maximumDeformation: (a float)
If Constrain Deformation is checked, limit the deformation to this
amount.
argument: ``--maximumDeformation %f``
default: (an integer (int or long))
Default pixel value used if resampling a pixel outside of the
volume.
argument: ``--default %d``
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.
argument: ``--initialtransform %s``
FixedImageFileName: (an existing file name)
Fixed image to which to register
argument: ``%s``, position: -2
MovingImageFileName: (an existing file name)
Moving image
argument: ``%s``, position: -1
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).
argument: ``--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.
argument: ``--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).
argument: ``--resampledmovingfilename %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
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¶
Wraps the executable 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:
[Optional]
fixedImage: (an existing file name)
Image which defines the space into which the moving image is
registered
argument: ``%s``, position: -2
movingImage: (an existing file name)
The transform goes from the fixed image's space into the moving
image's space
argument: ``%s``, position: -1
resampledImage: (a boolean or a file name)
Registration results
argument: ``--resampledImage %s``
loadTransform: (an existing file name)
Load a transform that is immediately applied to the moving image
argument: ``--loadTransform %s``
saveTransform: (a boolean or a file name)
Save the transform that results from registration
argument: ``--saveTransform %s``
initialization: ('None' or 'Landmarks' or 'ImageCenters' or
'CentersOfMass' or 'SecondMoments')
Method to prime the registration process
argument: ``--initialization %s``
registration: ('None' or 'Initial' or 'Rigid' or 'Affine' or
'BSpline' or 'PipelineRigid' or 'PipelineAffine' or
'PipelineBSpline')
Method for the registration process
argument: ``--registration %s``
metric: ('MattesMI' or 'NormCorr' or 'MeanSqrd')
Method to quantify image match
argument: ``--metric %s``
expectedOffset: (a float)
Expected misalignment after initialization
argument: ``--expectedOffset %f``
expectedRotation: (a float)
Expected misalignment after initialization
argument: ``--expectedRotation %f``
expectedScale: (a float)
Expected misalignment after initialization
argument: ``--expectedScale %f``
expectedSkew: (a float)
Expected misalignment after initialization
argument: ``--expectedSkew %f``
verbosityLevel: ('Silent' or 'Standard' or 'Verbose')
Level of detail of reporting progress
argument: ``--verbosityLevel %s``
sampleFromOverlap: (a boolean)
Limit metric evaluation to the fixed image region overlapped by the
moving image
argument: ``--sampleFromOverlap ``
fixedImageMask: (an existing file name)
Image which defines a mask for the fixed image
argument: ``--fixedImageMask %s``
randomNumberSeed: (an integer (int or long))
Seed to generate a consistent random number sequence
argument: ``--randomNumberSeed %d``
numberOfThreads: (an integer (int or long))
Number of CPU threads to use
argument: ``--numberOfThreads %d``
minimizeMemory: (a boolean)
Reduce the amount of memory required at the cost of increased
computation time
argument: ``--minimizeMemory ``
interpolation: ('NearestNeighbor' or 'Linear' or 'BSpline')
Method for interpolation within the optimization process
argument: ``--interpolation %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
argument: ``--fixedLandmarks %s...``
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
argument: ``--movingLandmarks %s...``
rigidMaxIterations: (an integer (int or long))
Maximum number of rigid optimization iterations
argument: ``--rigidMaxIterations %d``
rigidSamplingRatio: (a float)
Portion of the image to use in computing the metric during rigid
registration
argument: ``--rigidSamplingRatio %f``
affineMaxIterations: (an integer (int or long))
Maximum number of affine optimization iterations
argument: ``--affineMaxIterations %d``
affineSamplingRatio: (a float)
Portion of the image to use in computing the metric during affine
registration
argument: ``--affineSamplingRatio %f``
bsplineMaxIterations: (an integer (int or long))
Maximum number of bspline optimization iterations
argument: ``--bsplineMaxIterations %d``
bsplineSamplingRatio: (a float)
Portion of the image to use in computing the metric during BSpline
registration
argument: ``--bsplineSamplingRatio %f``
controlPointSpacing: (an integer (int or long))
Number of pixels between control points
argument: ``--controlPointSpacing %d``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
resampledImage: (an existing file name)
Registration results
saveTransform: (an existing file name)
Save the transform that results from registration
LinearRegistration¶
Wraps the executable 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:
[Optional]
fixedsmoothingfactor: (an integer (int or long))
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.
argument: ``--fixedsmoothingfactor %d``
movingsmoothingfactor: (an integer (int or long))
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.
argument: ``--movingsmoothingfactor %d``
histogrambins: (an integer (int or long))
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.
argument: ``--histogrambins %d``
spatialsamples: (an integer (int or long))
Number of spatial samples to use in estimating Mattes Mutual
Information. Larger values yield more accurate PDFs and improved
registration quality.
argument: ``--spatialsamples %d``
iterations: (a list of items which are an integer (int or long))
Comma separated list of iterations. Must have the same number of
elements as the learning rate.
argument: ``--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.
argument: ``--learningrate %s``
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.
argument: ``--translationscale %f``
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.
argument: ``--initialtransform %s``
FixedImageFileName: (an existing file name)
Fixed image to which to register
argument: ``%s``, position: -2
MovingImageFileName: (an existing file name)
Moving image
argument: ``%s``, position: -1
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).
argument: ``--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).
argument: ``--resampledmovingfilename %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
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¶
Wraps the executable 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:
[Optional]
fixedImage: (an existing file name)
Image which defines the space into which the moving image is
registered
argument: ``%s``, position: -2
movingImage: (an existing file name)
The transform goes from the fixed image's space into the moving
image's space
argument: ``%s``, position: -1
resampledImage: (a boolean or a file name)
Registration results
argument: ``--resampledImage %s``
saveTransform: (a boolean or a file name)
Save the output transform from the registration
argument: ``--saveTransform %s``
fixedImageMask: (an existing file name)
Label image which defines a mask of interest for the fixed image
argument: ``--fixedImageMask %s``
fixedImageROI: (a list of items which are any value)
Label image which defines a ROI of interest for the fixed image
argument: ``--fixedImageROI %s``
numIterations: (an integer (int or long))
Number of iterations to run at each resolution level.
argument: ``--numIterations %d``
numLineIterations: (an integer (int or long))
Number of iterations to run at each resolution level.
argument: ``--numLineIterations %d``
stepSize: (a float)
The maximum step size of the optimizer in voxels
argument: ``--stepSize %f``
stepTolerance: (a float)
The maximum step size of the optimizer in voxels
argument: ``--stepTolerance %f``
metricTolerance: (a float)
argument: ``--metricTolerance %f``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
Outputs:
resampledImage: (an existing file name)
Registration results
saveTransform: (an existing file name)
Save the output transform from the registration
RigidRegistration¶
Wraps the executable 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:
[Optional]
fixedsmoothingfactor: (an integer (int or long))
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.
argument: ``--fixedsmoothingfactor %d``
movingsmoothingfactor: (an integer (int or long))
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.
argument: ``--movingsmoothingfactor %d``
testingmode: (a boolean)
Enable testing mode. Input transform will be used to construct
floating image. The floating image will be ignored if passed.
argument: ``--testingmode ``
histogrambins: (an integer (int or long))
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.
argument: ``--histogrambins %d``
spatialsamples: (an integer (int or long))
Number of spatial samples to use in estimating Mattes Mutual
Information. Larger values yield more accurate PDFs and improved
registration quality.
argument: ``--spatialsamples %d``
iterations: (a list of items which are an integer (int or long))
Comma separated list of iterations. Must have the same number of
elements as the learning rate.
argument: ``--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.
argument: ``--learningrate %s``
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.
argument: ``--translationscale %f``
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.
argument: ``--initialtransform %s``
FixedImageFileName: (an existing file name)
Fixed image to which to register
argument: ``%s``, position: -2
MovingImageFileName: (an existing file name)
Moving image
argument: ``%s``, position: -1
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).
argument: ``--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).
argument: ``--resampledmovingfilename %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a
value of class 'str', nipype default value: {})
Environment variables
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).