Provided by: ants_2.2.0-1ubuntu1_amd64 bug

NAME

       ANTS - part of ANTS registration suite

DESCRIPTION

   COMMAND:
              ANTS

   OPTIONS:
       -x, --mask-image maskFileName

              this  mask  --  defined  in  the 'fixed' image space defines the region of interest over which the
              registration is computed ==> above 0.1 means inside mask ==> continuous values in range  [0.1,1.0]
              effect optimization like a probability. ==> values > 1 are treated as = 1.0

       -m, --image-metric

              The  metric  weights  are  relative  to the weights on the N other metrics passed to ANTS --- N is
              unlimited. So, the weight, w_i on the i^{th} metric will be w_i=w_i/ ( sum_i w_i ).Intensity-Based
              Metrics:

              CC/cross-correlation/CrossCorrelation[fixedImage,movingImage,weight,radius/OrForMI-#histogramBins]
              MI/mutual-information/MutualInformation[fixedImage,movingImage,weight,radius/OrForMI-#histogramBins]
              SMI/spatial-mutual-information/SpatialMutualInformation[fixedImage,movingImage,weight,radius/OrForMI-#histogramBins]
              PR/probabilistic/Probabilistic[fixedImage,movingImage,weight,radius/OrForMI-#histogramBins] SSD

       --- standard intensity difference.[fixedImage,movingImage,weight,radius/OrForMI-#histogramBins]

              MSQ/mean-squares/MeanSquares

       -- demons-like, radius > 0 uses moving image gradient in metric

              deriv.[fixedImage,movingImage,weight,radius/OrForMI-#histogramBins]

              Point-Set-Based Metrics:

              PSE/point-set-expectation/PointSetExpectation[fixedImage,movingImage,fixedPoints,movingPoints,weight,pointSetPercentage,pointSetSigma,boundaryPointsOnly,kNeighborhood,

       PartialMatchingIterations=100000]

              the partial matching option assumes the

              complete  labeling  is  in  the  first  set  of label parameters ... more iterations leads to more
              symmetry in the matching - 0 iterations means full asymmetry

              [fixedImage,movingImage,fixedPoints,movingPoints,weight,pointSetPercentage,pointSetSigma,boundaryPointsOnly,kNeighborhood,alpha,meshResolution,splineOrder,numberOfLevels,useAnisotropicCovariances]

       -o, --output-naming

              The name for the output - a prefix or a name+type : e.g. -o OUT or -o OUT.nii or -o OUT.mha

       --R

              TODO/FIXME:  the  --R  sets an ROI option -- it passes a vector of parameters that sets the center
              and bounding box

              of the region of interest for a sub-field

              registration. e.g. in 3D the option setting

       -r 10x12x15x50x50x25

              sets up a

              bounding box of size 50,50,25 with  origin  at  10,12,15  in  voxel  (should  this  be  physical?)
              coordinates.  <VALUES>: 0

       -i, --number-of-iterations

              number of iterations per level -- a 'vector' e.g. : 100x100x20 <VALUES>: 10x10x5

       --Restrict-Deformation

              restrict  the gradient that drives the deformation by scalar factors along specified dimensions --
              a TReal 'vector' of length ImageDimension to multiply against  the  similarity  metric's  gradient
              values  ---  e.g.  in 3D : 0.1x1x0 --- will set the z gradient to zero and scale the x gradient by
              0.1 and y by 1 (no change). Thus, you get a 2.5-Dimensional registration  as  there  is  still  3D
              continuity in the mapping.  <VALUES>: 1x1

       -v, --verbose

              verbose output

       --use-all-metrics-for-convergence

              enable  to  use weighted sum of all metric terms for convergence computation. By default, only the
              first metric is used <VALUES>: 0

       -h

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

       --help

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

       -t, --transformation-model

       TRANSFORMATION[gradient-step-length,number-of-time-steps,DeltaTime,symmetry-type].

       Choose one of the following TRANSFORMATIONS:

              Diff = diffeomorphic Elast =

              Elastic

              Exp = exponential diff

              Greedy Exp = greedy exponential diff, like

              diffeomorphic demons. same parameters.

              SyN -- symmetric normalization

              DeltaTime is the integration time-discretization step - sub-voxel - n-time steps  currently  fixed
              at 2 <VALUES>: SyN[0.5]

       -r, --regularization

              REGULARIZATION[gradient-field-sigma,def-field-sigma,truncation].

              Choose one of

              the following REGULARIZATIONS:

              Gauss = gaussian DMFFD = directly manipulated

              free form deformation <VALUES>: Gauss[3,0.5]

       -a, --initial-affine

              use the input file as the initial affine parameter

       -F, --fixed-image-initial-affine

              use the input file as the initial affine parameter for the fixed image

       --fixed-image-initial-affine-ref-image

              reference space for using the input file as the initial affine parameter for the fixed image

       -T, --geodesic

              = 0 / 1 / 2, 0 = not time-dependent, 1 = asymmetric , 2 = symmetric

       -G, --go-faster

              true  /  false  -- if true, SyN is faster but loses some accuracy wrt inverse-identity constraint,
              see Avants MIA 2008.  <VALUES>: false

       --continue-affine

              true (default) | false, do (not) perform affine given the initial affine parameters <VALUES>: true

       --number-of-affine-iterations

              number of iterations per level -- a 'vector' e.g. : 100x100x20 <VALUES>: 10000x10000x10000

       --use-NN

              use nearest neighbor interpolation <VALUES>: 0

       --use-Histogram-Matching

              use histogram matching of moving to fixed image <VALUES>: 0

       --affine-metric-type

              MI: mutual information (default), MSQ: mean square error, SSD, CC:  Normalized  correlation,  CCH:
              Histogram-based   correlation   coefficient   (not  recommended),  GD:  gradient  difference  (not
              recommended) <VALUES>: MI

       --MI-option

              option of mutual information: MI_bins x MI_samples (default: 32x32000) <VALUES>: 32x5000

       --rigid-affine

              use rigid transformation : true / false(default) <VALUES>: false

       --do-rigid

              use rigid transformation : true / false(default) <VALUES>: false

       --affine-gradient-descent-option

              option of gradient descent in affine transformation:  maximum_step_length  x  relaxation_factor  x
              minimum_step_length x translation_scales <VALUES>: 0.1x0.5x1.e-4x1.e-4

       --use-rotation-header

              use rotation matrix in image headers: true (default) / false <VALUES>: false

       --ignore-void-origin

              ignore the apparently unmatched origins (when use-rotation-header is false and the rotation matrix
              is identity: true (default) / false <VALUES>: false

       --gaussian-smoothing-sigmas

              At each resolution level the image is subsampled and smoothed by Gaussian convolution. This option
              allows the user to override the default smoothing by specifying sigma values (in mm) for smoothing
              both fixed and moving images for each resolution level.  <VALUES>:

       --subsampling-factors

              At each resolution level the image is subsampled and smoothed by Gaussian convolution. This option
              allows  the user to override the default subsampling by specifying the subsampling factor for both
              fixed and moving images for each resolution level.  <VALUES>: