mia-2dstack-cmeans-presegment - Online in the Cloud

PROGRAM:

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'.

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