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 -p controls the polynomial degree. -p 0 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 -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

OPTIONS:

-m, --metric CC[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random,None}>,<samplingPercentage=[0,1]>]

MI[fixedImage,movingImage,metricWeight,numberOfBins,<samplingStrategy={Regular,Random,None}>,<samplingPercentage=[0,1]>] MeanSquares[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random,None}>,<samplingPercentage=[0,1]>] GC[fixedImage,movingImage,metricWeight,radius,<samplingStrategy={Regular,Random,None}>,<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, --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 GenericLabel[<interpolator=Linear>]

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

-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.