Provided by: ants_2.2.0-1ubuntu1_amd64 bug


       antsSliceRegularizedRegistration - part of ANTS registration suite



              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 -p controls the polynomial
              degree. -p 0 means no regularization.Implemented by  B.  Avants  and  conceived  by
              Julien Cohen-Adad.


              OutputPrefixTxTy_poly.csv: polynomial fit to Tx &


              OutputPrefix.nii.gz: transformed image

       Example call:

              antsSliceRegularizedRegistration  -p  4 --output [OutputPrefix,OutputPrefix.nii.gz]
              --transform Translation[0.1] --metric MI[ fixed.nii.gz, moving.nii.gz , 1  ,  16  ,
              Regular , 0.2 ] --iterations 20 --shrinkFactors 1 --smoothingSigmas 0

       -m,                                                                               --metric


              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.

       -x, --mask mask-in-fixed-image-space.nii.gz

              Fixed image mask to limit voxels considered by the metric.

       -n, --interpolation Linear
              NearestNeighbor                        MultiLabel[<sigma=imageSpacing>,<alpha=4.0>]
              Gaussian[<sigma=imageSpacing>,<alpha=1.0>]  BSpline[<order=3>]   CosineWindowedSinc
              WelchWindowedSinc              HammingWindowedSinc              LanczosWindowedSinc

              Several interpolation options are available  in  ITK.  These  have  all  been  made

       -t, --transform Translation[gradientStep]
              Rigid[gradientStep] Similarity[gradientStep]

              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.

       -i, --iterations MxNx0...

              Specify the number of iterations at each level.

       -s, --smoothingSigmas MxNx0...

              Specify the amount of smoothing at each level.

       -f, --shrinkFactors MxNx0...

              Specify the shrink factor for the virtual domain (typically  the  fixed  image)  at
              each level.

       -o, --output [outputTransformPrefix,<outputWarpedImage>,<outputAverageImage>]

              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.

       -h, --help

              Print the help menu (short version).  <VALUES>: 1, 0

       -v, --verbose

              verbose option <VALUES>: 0

       -p, --polydegree

              degree  of polynomial - up to zDimension-2. Controls the polynomial degree. 0 means
              no regularization. This may  be  a  vector  denoted  by  2x2x1  for  a  3-parameter
              transform  (  e.g.  rigid  ).  This  would regularize the translation by 2nd degree
              polynomial and the rotation by a linear function.