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kellyslater(1) [debian man page]

KELLYSLATER(1)							   User Commands						    KELLYSLATER(1)

NAME
KellySlater - part of ANTS registration suite SYNOPSIS
KellySlater ImageDimension Segmentation.nii.gz WMProb.nii.gz GMProb.nii.gz Out.nii {GradStep-1-2D,2-3D} {#Its-~50} {ThickPriorValue-6} {Bool-use-curvature-prior} {smoothing} {BoolUseEuclidean?} DESCRIPTION
this is a kind of binary image registration thing with diffeomorphisms Segmentation.nii.gz -- should contain the value 3 where WM exists and the value 2 where GM exists KellySlater 1.9 May 2012 KELLYSLATER(1)

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ANTS(1) 							   User Commands							   ANTS(1)

NAME
ANTS - part of ANTS registration suite DESCRIPTION
Example usage: ./ANTS ImageDimension -m MI[fixedimage.nii.gz,movingimage.nii.gz,1,32] -o Outputfname.nii.gz -i 30x20x0 -r Gauss[3,1] -t Elast[3] Compulsory arguments: ImageDimension: 2 or 3 (for 2 or 3 Dimensional registration) -m: Type of similarity model used for registration. For intramodal image registration, use: CC = cross-correlation MI = mutual information PR = probability mapping MSQ = mean square difference For intermodal image registration, use: MI = mutual information PR = probability mapping -o Outputfname.nii.gz: the name of the resulting image. -i Max-iterations in format: JxKxL, where: J = max iterations at coarsest resolution (here, reduce by power of 2^2) K = middle resolution iterations (here,reduce by power of 2) L = fine resolution iterations (here, full resolution). This level takes much more time per iteration! Adding an extra value before JxKxL (i.e. resulting in IxJxKxL) would add another iteration level. -r Regularization -t Type of transformation model used for registration For elastic image registration, use: Elast = elastic transformation model (less deformation possible) For diffeomorphic image registration, use: Syn[GradStep,TimePoints,IntegrationStep] --geodesic 2 = SyN with time with arbitrary number of time points in time discretization SyN[GradStep,2,IntegrationStep] = SyN with time optimized specifically for 2 time points in the time discretization SyN[GradStep] = Greedy SyN, typicall GradStep=0.25 Exp[GradStep,TimePoints] = Exponential GreedyExp = Diffeomorphic Demons style exponential mapping Please use the `ANTS -h ` call or refer to the ANTS.pdf manual or antsIntroduction.sh script for additional information and typical values for transformation models ANTS 1.9 May 2012 ANTS(1)
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