NAME

       antsMotionCorr - part of ANTS registration suite

DESCRIPTION

   COMMAND:
              antsMotionCorr

              antsMotionCorr  =  motion  correction.  This  program  is a user-level registration
              application meant to utilize classes in ITK v4.0 or greater. The user  can  specify
              any  number of "stages" where a stage consists of a transform; an image metric; and
              iterations, shrink factors, and smoothing sigmas for each level.   Specialized  for
              4D  time series data: fixed image is 3D, moving image should be the 4D time series.
              Fixed image is a reference space or time slice.

   OPTIONS:
       -d, --dimensionality 2/3

              This option forces the image to be treated as a specified-dimensional image. If not
              specified, the program tries to infer the dimensionality from the input image.

       -n, --n-images 10

              This option sets the number of images to use to construct the template image.

       -m,                                                                               --metric
              CC[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>,<useGradientFilter=false>]

              MI[fixedImage,movingImage,metricWeight,numberOfBins,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>,<useGradientFilter=false>]
              Demons[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>,<useGradientFilter=false>]
              GC[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>,<useGradientFilter=false>]

              Four image metrics are available--- GC : global correlation, CC: ANTS  neighborhood
              cross  correlation,  MI: Mutual information, and Demons: Thirion's Demons (modified
              mean-squares). Note that the metricWeight is currently not used. Rather,  it  is  a
              temporary place holder until multivariate metrics are available for a single stage.
              The fixed image should be a single time point (eg the average of the time  series).
              By  default,  this image is not used, the fixed image for correction of each volume
              is the preceding volume in the time series.  See below for  the  option  to  use  a
              fixed  reference  image  for  all  volumes.   useGradientFilter specifies whether a
              smoothingfilter is applied when estimating the metric gradient.

       -u, --useFixedReferenceImage (0)/1

              use a fixed reference image to correct all  volumes,  instead  of  correcting  each
              image to the prior volume in the time series.

       -e, --useScalesEstimator

              use the scale estimator to control optimization.

       -t, --transform Affine[gradientStep]
              Rigid[gradientStep]
              GaussianDisplacementField[gradientStep,updateFieldSigmaInPhysicalSpace,totalFieldSigmaInPhysicalSpace]
              SyN[gradientStep,updateFieldSigmaInPhysicalSpace,totalFieldSigmaInPhysicalSpace]

              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 sigma for smoothing at each level. Smoothing may  be  specified  in  mm
              units or voxels with "AxBxCmm" or "AxBxCvox". No units implies voxels.

       -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.

       -a, --average-image

              Average the input time series image.

       -w, --write-displacement

              Write the low-dimensional 3D transforms to a 4D displacement field.

       --use-histogram-matching 0/(1)

              Histogram match the moving images to the reference image.

       --random-seed seedValue

              Use a fixed seed for random number generation. By default, the system clock is used
              to initialize the seeding. The fixed seed can be any nonzero int value.

       -p, --interpolation Linear
              NearestNeighbor    BSpline[<order=3>]    BlackmanWindowedSinc    CosineWindowedSinc
              WelchWindowedSinc HammingWindowedSinc LanczosWindowedSinc

              Several interpolation options  are  available  in  ITK.  The  above  are  available
              (default Linear).

       -v, --verbose (0)/1

              Verbose output.

       -h

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

       --help

              Print the help menu.  <VALUES>: 1, 0