DESCRIPTIONAverage segmentations (label fields) using the Euclidean Distance Transform. All input images must be in the same space. EDT is computed in this space also. See http://dx.doi.org/10.1109/TIP.2006.884936 for details of the underlying algorithm.
Global Toolkit Options (these are shared by all CMTK tools)
- 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.
- --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).
- --num-labels <integer>, -n <integer>
- Number of labels. It is assumed that only values [0..num] occur in the images [Default: 0]
- --padding <float>, -p <float>
- Padding value in input image [Default: disabled]
Label Combination Options
- --exclude-outliers, -x
- Exclude local outliers in the shape-based averaging algorithm. Outliers at each pixel are defined as those input images for which the distance from the nearest pixel with the current label exceeds thresholds computed from the set of distances over all inputs.
- --output <string>, -o <string>
- File name for output segmentation file. [Default: sba.nii]
AUTHORSTorsten Rohlfing, with contributions from Michael P. Hasak, Greg Jefferis, Calvin R. Maurer, Daniel B. Russakoff, and Yaroslav Halchenko
BUGSReport bugs at http://nitrc.org/projects/cmtk/
ACKNOWLEDGMENTSCMTK 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.