DOKK / manpages / debian 12 / cmtk / cmtk-groupwise_warp.1.en
groupwise_warp(1) The Computational Morphometry Toolkit groupwise_warp(1)

groupwise_warp - Nonrigid population registration

groupwise_warp [options] affineGroupRegistration

This tool nonrigidly registers a population of input images simultaneously, without a template, using either the 'congealing' algorithm or a groupwise similarity measure based on a continuous approximation of mutual information ('RMI').

Write list of basic command line options to standard output.
Write complete list of basic and advanced command line options to standard output.
Write list of command line options to standard output in MediaWiki markup.
Write man page source in 'nroff' markup to standard output.
Write toolkit version to standard output.
Write the current command line to standard output.
Set verbosity level.
Increment verbosity level by 1 (deprecated; supported for backward compatibility).
Set maximum number of parallel threads (for POSIX threads and OpenMP).

Use the RMI (a.k.a. regional mutual information) metric to drive the registration).
Use the congealing algorithm using pixelwise stack entropies to drive the registration. [This is the default]

Override template image with given file. [Default: NONE]
Use user-supplied template images's pixel data in registration [Default: disabled]

Initial downsampling factor [4]. [Default: 4]
Final downsampling factor [1]. [Default: 1]
Probabilistic sampling density [default: off]. [Default: -1]

Root directory for all output files. [Default: NONE]
Output filename for groupwise registration archive. [Default: groupwise.xforms ]
Output filename for registered average image. [Default: average.nii ]
Do not write average image.
Use cubic interpolation for average image (default: linear)

Force background pixels (outside FOV) to given (bin) value. [Default: disabled]
Set number of histogram bins for entropy evaluation. [Default: disabled]
Crop image histograms to make better use of histogram bins.
Match all image histograms to template data (or first image, if no template image is given)
Frequetly repeat histogram-based intensity matching to account for changing volume proportions.
Sigma of Gaussian smoothing kernel in multiples of template image pixel size [Default: disabled]
Sigma of Gaussian smoothing kernel in multiples of control point delta [Default: disabled]

Control point grid spacing. [Default: 40]
Use grid spacing that fits volume FOV
Number of times to refine transformation grid [default: 0]. [Default: 0]

Enforce zero-sum computation.
Enforce zero-sum computation EXCLUDING affine components.
First N images are from the normal group and should be registered unbiased. [Default: 0]
Enforce zero-sum computation for first N images. [Default: disabled]
Weight for Jacobian volume preservation constraint [default: off] [Default: 0]
Weight for grid bending energy regularization constraint [default: off] [Default: 0]

Exploration of optimization in pixels [Default: 0.25]
Accuracy of optimization in pixels [Default: 0.01]
Step factor for successive optimization passes [Default: 0.5]
Optional threshold to terminate optimization (level) if relative change of target function drops below this value. [Default: 0]
Threshold factor for partial gradient zeroing [<0 turn off] [Default: 0]
Activate potentially uninformative control points
Path to mask image (matching template grid) defining areas in which control points should be disabled. This guarantees that mask foreground areas remain undeformed. [Default: NONE]
Disable optimization and output initial configuration.

Torsten Rohlfing, with contributions from Michael P. Hasak, Greg Jefferis, Calvin R. Maurer, Daniel B. Russakoff, and Yaroslav Halchenko

http://www.fsf.org/licensing/licenses/gpl.html

Report bugs at http://nitrc.org/projects/cmtk/

CMTK is developed with support from the NIAAA under Grant AA021697, National Consortium on Alcohol and Neurodevelopment in Adolescence (N-CANDA): Data Integration Component. From April 2009 through September 2011, CMTK development and maintenance was supported by the NIBIB under Grant EB008381.

Jun 6 2022 CMTK 3.3.1p2