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

levelset - Levelset segmentation

levelset InputImage OutputImage

Levelset-type segmentation of foreground/background using minimum regional variance energy

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

Binarize levelset and write as byte mask, rather than write floating-point levelset function itself.

Scale factor to reduce or increase the size of the initial foreground region sphere. [Default: 1]

Maximum number of iterations [Default: 100]
Force given number of iterations, even when convergence has been detected
Gaussian filter sigma in world coordinate units (e.g., mm) [Default: 2]
Time constant for levelset evolution; must be > 0; larger is faster [Default: 0.1]
Levelset threshold: levelset function is truncated at +/- this value [Default: 1]

Path to image/transformation database that should be updated with the newly created image. [Default: NONE]

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