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mia-2dstack-cmeans-presegment(1) General Commands Manual mia-2dstack-cmeans-presegment(1)

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

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

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.

input image(s) to be filtered
For supported file types see PLUGINS:2dimage/io
Save probability map to this file

output file name type

output file name base

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
print copyright information

print this help

-? --usage
print a short help

print the version number and exit

Percent of the extrem parts of the histogram to be collapsed into the respective last histogram bin.

C-means class initializer
For supported plugins see PLUGINS:1d/cmeans
Probability threshold value to consider a pixel as seed pixel.

Class label to create the mask from

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).

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.

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.

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]).

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

Virtual IO to and from the internal data pool

Recognized file extensions: .@

2D image io for DICOM

Recognized file extensions: .DCM, .dcm

Supported element types:
signed 16 bit, unsigned 16 bit

a 2dimage io plugin for OpenEXR images

Recognized file extensions: .EXR, .exr

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

a 2dimage io plugin for jpeg gray scale images

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

Supported element types:
unsigned 8 bit

a 2dimage io plugin for png images

Recognized file extensions: .PNG, .png

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

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

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

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

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

Gert Wollny

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'.

v2.4.7 USER COMMANDS