Provided by: ants_2.2.0-1ubuntu1_amd64

**NAME**

antsSliceRegularizedRegistration - part of ANTS registration suite

**DESCRIPTION**

COMMAND:antsSliceRegularizedRegistration 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-pcontrols the polynomial degree.-p0 means no regularization.Implemented by B. Avants and conceived by Julien Cohen-Adad. Outputs: OutputPrefixTxTy_poly.csv: polynomial fit to Tx & Ty OutputPrefix.nii.gz: transformed image Example call: antsSliceRegularizedRegistration-p4--output[OutputPrefix,OutputPrefix.nii.gz]--transformTranslation[0.1]--metricMI[ fixed.nii.gz, moving.nii.gz , 1 , 16 , Regular , 0.2 ]--iterations20--shrinkFactors1--smoothingSigmas0OPTIONS:-m,--metricCC[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>] MI[fixedImage,movingImage,metricWeight,numberOfBins,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>] MeanSquares[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>] GC[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random}>,<samplingPercentage=[0,1]>] 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,--maskmask-in-fixed-image-space.nii.gz Fixed image mask to limit voxels considered by the metric.-n,--interpolationLinear NearestNeighbor MultiLabel[<sigma=imageSpacing>,<alpha=4.0>] Gaussian[<sigma=imageSpacing>,<alpha=1.0>] BSpline[<order=3>] CosineWindowedSinc WelchWindowedSinc HammingWindowedSinc LanczosWindowedSinc GenericLabel[<interpolator=Linear>] Several interpolation options are available in ITK. These have all been made available.-t,--transformTranslation[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,--iterationsMxNx0... Specify the number of iterations at each level.-s,--smoothingSigmasMxNx0... Specify the amount of smoothing at each level.-f,--shrinkFactorsMxNx0... 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,--helpPrint the help menu (short version). <VALUES>: 1, 0-v,--verboseverbose option <VALUES>: 0-p,--polydegreedegree 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.