Provided by: mia-tools_2.2.7-3_amd64 bug

NAME

       mia-2dstack-cmeans-presegment  -  Pre-classify  the  input image series by using a c-means
       estimator

SYNOPSIS

       mia-2dstack-cmeans-presegment -i <in-file> -o <out-mask> -L <label> [options]

DESCRIPTION

       mia-2dstack-cmeans-presegment This program first evaluates a sparse histogram of an  input
       image  series,  then  runs a c-means classification over the histogram, and then estimates
       the mask for one (given) class based on class probabilities.  This  program  accepts  only
       images of eight or 16 bit integer pixels.

OPTIONS

   File-IO
              -i --in-file=(input, required); io
                     input   image(s)   to   be   filtered    For   supported   file   types  see
                     PLUGINS:2dimage/io

              -p --out-probmap=(output); string
                     Save probability map to this file

              -t --type=png
                     output file name type

              -o --out-mask=(output, required); string
                     output file name base

   Help & Info
              -V --verbose=warning
                     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
                        warning ‐ Warnings
                        error ‐ Report errors
                        debug ‐ Debug output
                        message ‐ Normal messages
                        fatal ‐ Report only fatal errors

                 --copyright
                     print copyright information

              -h --help
                     print this help

              -? --usage
                     print a short help

                 --version
                     print the version number and exit

   Parameters
              -T --histogram-thresh=5; float in [0, 50]
                     Percent  of  the  extrem  parts  of  the  histogram to be collapsed into the
                     respective last histogram bin.

              -C --classes=kmeans:nc=3
                     C-means class initializerC-means class initializer   For  supported  plugins
                     see PLUGINS:1d/cmeans

              -S --seed-threshold=0.95; float in (0, 1)
                     Probability threshold value to consider a pixel as seed pixel.

              -L --label=(required); int in [0, 10]
                     Class label to create the mask fromClass label to create the mask from

   Processing
                 --threads=-1
                     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).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).

PLUGINS: 1d/cmeans

       even      C-Means  initializer  that  sets the initial class centers as evenly distributed
                 over [0,1], supported parameters are:

                     nc =(required, ulong)
                       Number of classes to use for the fuzzy-cmeans classification.

       kmeans    C-Means initializer that sets the initial  class  centers  by  using  a  k-means
                 classification, supported parameters are:

                     nc =(required, ulong)
                       Number of classes to use for the fuzzy-cmeans classification.

       predefined
                 C-Means  initializer that sets pre-defined values for the initial class centers,
                 supported parameters are:

                     cc =(required, vdouble)
                       Initial class centers fuzzy-cmeans  classification  (normalized  to  range
                       [0,1]).

PLUGINS: 2dimage/io

       bmp       BMP 2D-image input/output support

                     Recognized file extensions:  .BMP, .bmp

                     Supported element types:
                       binary data, unsigned 8 bit, unsigned 16 bit

       datapool  Virtual IO to and from the internal data pool

                     Recognized file extensions:  .@

       dicom     2D image io for DICOM

                     Recognized file extensions:  .DCM, .dcm

                     Supported element types:
                       signed 16 bit, unsigned 16 bit

       exr       a 2dimage io plugin for OpenEXR images

                     Recognized file extensions:  .EXR, .exr

                     Supported element types:
                       unsigned 32 bit, floating point 32 bit

       jpg       a 2dimage io plugin for jpeg gray scale images

                     Recognized file extensions:  .JPEG, .JPG, .jpeg, .jpg

                     Supported element types:
                       unsigned 8 bit

       png       a 2dimage io plugin for png images

                     Recognized file extensions:  .PNG, .png

                     Supported element types:
                       binary data, unsigned 8 bit, unsigned 16 bit

       raw       RAW 2D-image output support

                     Recognized file extensions:  .RAW, .raw

                     Supported element types:
                       binary data, signed 8 bit, unsigned 8 bit, signed 16 bit, unsigned 16 bit,
                       signed 32 bit, unsigned 32 bit, floating point 32 bit, floating  point  64
                       bit

       tif       TIFF 2D-image input/output support

                     Recognized file extensions:  .TIF, .TIFF, .tif, .tiff

                     Supported element types:
                       binary data, unsigned 8 bit, unsigned 16 bit, unsigned 32 bit

       vista     a 2dimage io plugin for vista images

                     Recognized file extensions:  .V, .VISTA, .v, .vista

                     Supported element types:
                       binary data, signed 8 bit, unsigned 8 bit, signed 16 bit, unsigned 16 bit,
                       signed 32 bit, unsigned 32 bit, floating point 32 bit, floating  point  64
                       bit

EXAMPLE

       Run  the  program over images imageXXXX.png with the sparse histogram, threshold the lower
       30% bins (if available), run cmeans with two classes  on  the  non-zero  pixels  and  then
       create the mask for class 1 as foregroundXXXX.png.

       mia-2dstack-cmeans-presegment  -i  imageXXXX.png -o foreground -t png --histogram-tresh=30
              --classes 2 --label 1

AUTHOR(s)

       Gert Wollny

COPYRIGHT

       This software is Copyright (c) 1999‐2015 Leipzig, Germany and  Madrid,  Spain.   It  comes
       with   ABSOLUTELY   NO  WARRANTY  and  you  may redistribute it under the terms of the GNU
       GENERAL PUBLIC LICENSE Version 3 (or later). For more information run the program with the
       option '--copyright'.