table of contents
| mia-2dstack-cmeans-presegment(1) | General Commands Manual | mia-2dstack-cmeans-presegment(1) |
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=(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:
- --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:
- kmeans
- C-Means initializer that sets the initial class centers by using a k-means classification, supported parameters are:
- predefined
- C-Means initializer that sets pre-defined values for the initial class centers, supported parameters are:
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.
- datapool
- Virtual IO to and from the internal data pool
- dicom
- 2D image io for DICOM
- exr
- a 2dimage io plugin for OpenEXR images
- jpg
- a 2dimage io plugin for jpeg gray scale images
- png
- a 2dimage io plugin for png images
- raw
- RAW 2D-image output support
- tif
- TIFF 2D-image input/output support
- vista
- a 2dimage io plugin for vista images
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'.
| v2.4.7 | USER COMMANDS |