mia-2dsegment-ahmed

Sysnopis:

mia-2dsegment-ahmed {-i io} {-o io} [ options ...]

Description:

This program implements a variation of the paper:

Mohamed N. Ahmed et. al, "A Modified Fuzzy C-Means Algorithm for Bias Field estimation and Segmentation of MRI Data", IEEE Trans. on Medical Imaging, Vol. 21, No. 3, March 2002,

changes are: p=2, and exp

Options:

-i, --in-file=(input, required); io

image to be segmented. For supported file types see Plugin type: 2dimage/io

-o, --out-file=(required, output); io

class probability images, the image type must support multiple images and floating point values. For supported file types see Plugin type: 2dimage/io

-a, --no-of-classes=3; int

number of classes

-b, --bias-correct

apply bias field correction

-c, --class-centres=

initial class centers

-s, --spread=64; float

spread parameter describing the strength of mattar distinction

Help & Info

-V, --verbose=warning; dict

verbosity of output, print messages of given level and higher priorities. Supported priorities starting at lowest level are:

debug:Debug output
message:Normal messages
info:Low level messages
error:Report errors
fatal:Report only fatal errors
trace:Function call trace
warning:Warnings
fail:Report test failures
--copyright=(); bool

print copyright information

-h, --help=(); bool

print this help

-?, --usage=(); bool

print a short help

--version=(); bool

print the version number and exit

Processing

--threads=-1; int

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).

Example:

Run a 5-class segmentation over input image input.v and store the class probability images in cls.v.

mia-2dsegment-ahmed -i input.v -a 5 -o cls.v

Author(s):

Gert Wollny