WARPIMAGEMULTITRANSFORM(1) User Commands WARPIMAGEMULTITRANSFORM(1)NAME
WarpImageMultiTransform - part of ANTS registration suite
DESCRIPTION
Usage:
./WarpImageMultiTransform ImageDimension moving_image output_image -R reference_image --use-NN SeriesOfTransformations--(See Below)
SeriesOfTransformations --- ./WarpImageMultiTransform can apply, via concatenation, an unlimited number of transformations to your
data . Thus, SeriesOfTransformations may be an Affine transform followed by a warp another affine and then another warp.
Inverse affine transformations are invoked by calling
-i MyAffine.txt
InverseWarps are invoked by passing the InverseWarp.nii.gz
filename (see below for a note about this).
Example 1: Mapping a warped image into the reference_image domain by applying abcdWarpxvec.nii.gz/abcdWarpyvec.nii.gz/abcd-
Warpzvec.nii.gz and then abcdAffine.txt
./WarpImageMultiTransform 3 moving_image output_image -R reference_image abcdWarp.nii.gz abcdAffine.txt
Example 2: To map the fixed/reference_image warped into the moving_image domain by applying the inversion of abcdAffine.txt and then
abcdInverseWarpxvec.nii.gz/abcdInverseWarpyvec.nii.gz/abcdInverseWarpzvec.nii.gz .
./WarpImageMultiTransform 3 reference_image output_image -R moving_image -i abcdAffine.txt abcdInverseWarp.nii.gz
Note that the inverse maps (Ex. 2) are passed to this program in the reverse order of the forward maps (Ex. 1).
This makes sense, geometrically ... see ANTS.pdf for visualization of this syntax.
Compulsory arguments:
ImageDimension: 2 or 3 (for 2 or 3 Dimensional registration)
moving_image: the image to apply the transformation to
output_image: the resulting image
Optional arguments:
-R: reference_image space that you wish to warp INTO.
--tightest-bounding-box: Computes the tightest bounding box using all the affine transformations. It will be overrided by -R refer-
ence_image if given. --reslice-by-header: equivalient to -i -mh, or -fh -i -mh if used together with -R. It uses the orientation
matrix and origin encoded in the image file header. It can be used together with -R. This is typically not used together with any
other transforms.
--use-NN: Use Nearest Neighbor Interpolation.
--use-BSpline: Use 3rd order B-Spline Interpolation.
-i: will use the inversion of the following affine transform.
Other Example Usages: Reslice the image: WarpImageMultiTransform 3 Imov.nii.gz Iout.nii.gz --tightest-bounding-box
--reslice-by-header Reslice the image to a reference image: WarpImageMultiTransform 3 Imov.nii.gz Iout.nii.gz -R Iref.nii.gz
--tightest-bounding-box --reslice-by-header
Important Notes: Prefixname "abcd" without any extension will use ".nii.gz" by default The abcdWarp and abcdInverseWarp do not
exist. They are formed on the basis of abcd(Inverse)Warpxvec/yvec/zvec.nii.gz when calling ./WarpImageMultiTransform, yet you have
to use them as if they exist.
WarpImageMultiTransform 1.9 May 2012 WARPIMAGEMULTITRANSFORM(1)
Check Out this Related Man Page
ANTS(1) User Commands ANTS(1)NAME
ANTS - part of ANTS registration suite
DESCRIPTION
Example usage:
./ANTS ImageDimension -m MI[fixedimage.nii.gz,movingimage.nii.gz,1,32] -o Outputfname.nii.gz -i 30x20x0 -r Gauss[3,1] -t Elast[3]
Compulsory arguments:
ImageDimension: 2 or 3 (for 2 or 3 Dimensional registration)
-m: Type of similarity model used for registration.
For intramodal image registration, use:
CC = cross-correlation MI = mutual information PR = probability mapping MSQ = mean square difference
For intermodal image registration, use:
MI = mutual information PR = probability mapping
-o Outputfname.nii.gz: the name of the resulting image.
-i Max-iterations in format: JxKxL, where:
J = max iterations at coarsest resolution (here, reduce by power of 2^2) K = middle resolution iterations (here,reduce by power of
2) L = fine resolution iterations (here, full resolution). This level takes much more time per iteration!
Adding an extra value before JxKxL (i.e. resulting in IxJxKxL) would add another iteration level.
-r Regularization
-t Type of transformation model used for registration
For elastic image registration, use:
Elast = elastic transformation model (less deformation possible)
For diffeomorphic image registration, use:
Syn[GradStep,TimePoints,IntegrationStep] --geodesic 2 = SyN with time with arbitrary number of time points in time discretization
SyN[GradStep,2,IntegrationStep] = SyN with time optimized specifically for 2 time points in the time discretization SyN[GradStep] =
Greedy SyN, typicall GradStep=0.25 Exp[GradStep,TimePoints] = Exponential GreedyExp = Diffeomorphic Demons style exponential mapping
Please use the `ANTS -h ` call or refer to the ANTS.pdf manual or antsIntroduction.sh script for additional information and typical
values for transformation models
ANTS 1.9 May 2012 ANTS(1)