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