antsSliceRegularizedRegistration(1)
NAME
antsSliceRegularizedRegistration - part of ANTS registration suite
DESCRIPTION
COMMAND:
antsSliceRegularizedRegistration
antsSliceRegularizedRegistration This program is a user-level
application for slice-by-slice translation registration. Results
are regularized in z using polynomial regression. The program is
targeted at spinal cord MRI. Only one stage is supported where a
stage consists of a transform; an image metric; and iterations,
shrink factors, and smoothing sigmas for each level. Specialized
for 3D data: fixed image is 3D, moving image is 3D. Registration
is performed slice-by-slice then regularized in z. The parameter
-p controls the polynomial degree. -p 0 means no
regularization.Implemented by B. Avants and conceived by Julien
Cohen-Adad.
Outputs:
OutputPrefixTxTy_poly.csv: polynomial fit to Tx &
Ty
OutputPrefix.nii.gz: transformed image
Example call:
antsSliceRegularizedRegistration -p 4 --output
[OutputPrefix,OutputPrefix.nii.gz] --transform Translation[0.1]
--metric MI[ fixed.nii.gz, moving.nii.gz , 1 , 16 , Regular ,
0.2 ] --iterations 20 --shrinkFactors 1 --smoothingSigmas 0
OPTIONS:
-m, --metric
CC[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>]
MI[fixedImage,movingImage,metricWeight,numberOfBins,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>]
MeanSquares[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>]
GC[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>]
Four image metrics are available--- GC : global correlation, CC:
ANTS neighborhood cross correlation, MI: Mutual information, and
MeanSquares: mean-squares intensity difference. Note that the
metricWeight is currently not used. Rather, it is a temporary
place holder until multivariate metrics are available for a
single stage.
-x, --mask mask-in-fixed-image-space.nii.gz
Fixed image mask to limit voxels considered by the metric.
-n, --interpolation Linear
NearestNeighbor MultiLabel[<sigma=imageSpacing>,<alpha=4.0>]
Gaussian[<sigma=imageSpacing>,<alpha=1.0>] BSpline[<order=3>]
CosineWindowedSinc WelchWindowedSinc HammingWindowedSinc
LanczosWindowedSinc
Several interpolation options are available in ITK. These have
all been made available.
-t, --transform Translation[gradientStep]
Several transform options are available. The gradientStep
orlearningRate characterizes the gradient descent optimization
and is scaled appropriately for each transform using the shift
scales estimator. Subsequent parameters are transform-specific
and can be determined from the usage.
-i, --iterations MxNx0...
Specify the number of iterations at each level.
-s, --smoothingSigmas MxNx0...
Specify the amount of smoothing at each level.
-f, --shrinkFactors MxNx0...
Specify the shrink factor for the virtual domain (typically the
fixed image) at each level.
-o, --output
[outputTransformPrefix,<outputWarpedImage>,<outputAverageImage>]
Specify the output transform prefix (output format is .nii.gz
).Optionally, one can choose to warp the moving image to the
fixed space and, if the inverse transform exists, one can also
output the warped fixed image.
-h, --help
Print the help menu (short version). <VALUES>: 1, 0
-v, --verbose
verbose option <VALUES>: 0
-p, --polydegree
degree of polynomial - up to zDimension-2. Controls the
polynomial degree. 0 means no regularization.
antsSliceRegularizedRegistration 2August 20ANTSSLICEREGULARIZEDREGISTRATION(1)
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