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=(required, input); 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=(required, output); 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:

                        trace ‐ Function call trace
                        debug ‐ Debug output
                        info ‐ Low level messages
                        message ‐ Normal messages
                        warning ‐ Warnings
                        fail ‐ Report test failures
                        error ‐ Report errors
                        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 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 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).

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. The plug-in supports reading and writing of
                 binary images and 8-bit gray scale images. read-only  support  is  provided  for
                 4-bit  gray  scale  images.  The color table is ignored and the pixel values are
                 taken as literal gray scale values.

                     Recognized file extensions:  .BMP, .bmp

                     Supported element types:
                       binary data, unsigned 8 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'.