This program is a implementation of a fuzzy c-means segmentation algorithm
image to be segmented. For supported file types see Plugin type: 2dimage/io
class probability images, the image type must support multiple images and floating point values. For supported file types see Plugin type: 2dimage/io
B-field corrected image. For supported file types see Plugin type: 2dimage/io
Logarithmic gain field, the image type must support floating point values. For supported file types see Plugin type: 2dimage/io
verbosity of output, print messages of given level and higher priorities. Supported priorities starting at lowest level are:
|info:||Low level messages|
|trace:||Function call trace|
|fail:||Report test failures|
|fatal:||Report only fatal errors|
print copyright information
print this help
print a short help
print the version number and exit
Maxiumum number of threads to use for processing,This number should be lower or equal to the number of logical processor cores in the machine. (-1: automatic estimation).
number of classes to segment
initial class centers
neighborhood filter for B-field correction. For supported plug-ins see Plugin type: 2dimage/filter
weight of neighborhood filter for B-field correction
parameter describing the fuzzyness of mattar distinction
Stopping criterion for class center estimation.
Run a 5-class segmentation over inpt image input.v and store the class probability images in cls.v.
mia-2dsegment-fuzzyw -i input.v -a 5 -o cls.v