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'.