gmm - Gaussian mixture model segmentation

       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.

CMTK 3.3.1p2                                       Feb 26 2025                                            gmm(1)

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

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

       Segment an image into c classes using the EM algorithm for Gaussian mixtures with optional priors.

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

       gmm - Gaussian mixture model segmentation

GlobalToolkitOptions(thesearesharedbyallCMTKtools)--help
            Write list of basic command line options to standard output.

       --help-all
            Write complete list of basic and advanced command line options to standard output.

       --wiki
            Write list of command line options to standard output in MediaWiki markup.

       --man
            Write man page source in 'nroff' markup to standard output.

       --xml
            Write command line syntax specification in XML markup (for Slicer integration).

       --version
            Write toolkit version to standard output.

       --echo
            Write the current command line to standard output.

       --verbose-level<integer>
            Set verbosity level.

       --verbose, -v
            Increment verbosity level by 1 (deprecated; supported for backward compatibility).

       --threads<integer>
            Set maximum number of parallel threads (for POSIX threads and OpenMP).

   GeneralClassificationParameters--mask<string>, -m<string>
            Path to foreground mask image. If this is not provided, the input image is used as its own mask, but
            this  does  not  work  properly  if  the input image itself has pixels with zero or negative values.
            [Default:NONE]--classes<integer>, -c<integer>
            Number of classes.  [Default:3]--iterations<integer>, -n<integer>
            Number of EM iterations.  [Default:10]HandlingofPriors--priors-init-only
            Use priors for initialization only.

       --prior-epsilon<double>, -e<double>
            Small value to add to all class priors to eliminate zero priors.  [Default:0]OutputParameters--probability-maps, -p
            Write probability maps. The file names for these maps will be generated from the output  image  path
            by inserting '_prob#' before the file format suffix, where '#' is the index of the respective class,
            numbered starting at 1 (zero is background).

gmm InputImage OutputImage PriorImages