.\" DO NOT MODIFY THIS FILE!  It was generated by help2man 1.47.4.
.TH ANTSSLICEREGULARIZEDREGISTRATION "1" "September 2017" "antsSliceRegularizedRegistration 2.1.0" "User Commands"
.SH NAME
antsSliceRegularizedRegistration \- part of ANTS registration suite
.SH DESCRIPTION
.SS "COMMAND:"
.IP
antsSliceRegularizedRegistration
.IP
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 \fB\-p\fR controls the polynomial
degree. \fB\-p\fR 0 means no regularization.Implemented by B. Avants and conceived by
Julien Cohen\-Adad.
.PP
Outputs:
.IP
OutputPrefixTxTy_poly.csv: polynomial fit to Tx &
.IP
Ty
.IP
OutputPrefix.nii.gz: transformed image
.PP
Example call:
.IP
antsSliceRegularizedRegistration \fB\-p\fR 4 \fB\-\-output\fR
[OutputPrefix,OutputPrefix.nii.gz] \fB\-\-transform\fR Translation[0.1] \fB\-\-metric\fR MI[
fixed.nii.gz, moving.nii.gz , 1 , 16 , Regular , 0.2 ] \fB\-\-iterations\fR 20
\fB\-\-shrinkFactors\fR 1 \fB\-\-smoothingSigmas\fR 0
.SS "OPTIONS:"
.HP
\fB\-m\fR, \fB\-\-metric\fR CC[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>]
.IP
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]>]
.IP
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.
.HP
\fB\-x\fR, \fB\-\-mask\fR mask\-in\-fixed\-image\-space.nii.gz
.IP
Fixed image mask to limit voxels considered by the metric.
.TP
\fB\-n\fR, \fB\-\-interpolation\fR Linear
NearestNeighbor
MultiLabel[<sigma=imageSpacing>,<alpha=4.0>]
Gaussian[<sigma=imageSpacing>,<alpha=1.0>]
BSpline[<order=3>]
CosineWindowedSinc
WelchWindowedSinc
HammingWindowedSinc
LanczosWindowedSinc
.IP
Several interpolation options are available in ITK. These have all been made
available.
.HP
\fB\-t\fR, \fB\-\-transform\fR Translation[gradientStep]
.IP
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.
.HP
\fB\-i\fR, \fB\-\-iterations\fR MxNx0...
.IP
Specify the number of iterations at each level.
.HP
\fB\-s\fR, \fB\-\-smoothingSigmas\fR MxNx0...
.IP
Specify the amount of smoothing at each level.
.HP
\fB\-f\fR, \fB\-\-shrinkFactors\fR MxNx0...
.IP
Specify the shrink factor for the virtual domain (typically the fixed image) at
each level.
.HP
\fB\-o\fR, \fB\-\-output\fR [outputTransformPrefix,<outputWarpedImage>,<outputAverageImage>]
.IP
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.
.HP
\fB\-h\fR, \fB\-\-help\fR
.IP
Print the help menu (short version).
<VALUES>: 1, 0
.HP
\fB\-v\fR, \fB\-\-verbose\fR
.IP
verbose option
<VALUES>: 0
.HP
\fB\-p\fR, \fB\-\-polydegree\fR
.IP
degree of polynomial \- up to zDimension\-2. Controls the polynomial degree. 0
means no regularization.