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