Man Linux: Main Page and Category List


       ANTS - part of ANTS registration suite


       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  script  for  additional information and
              typical values for transformation models