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. To create a reference image from  the
              time series, use the -a option.

   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 <timeseries>

              Average the input time series image.

       -w, --write-displacement (0)/1

              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

antsMotionCorr 2.5.4+dfsg                         February 2025                                ANTSMOTIONCORR(1)