Difference between revisions of "Modules:FuzzySegmentationModule"
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| + | This module computes voxel by voxel tissue classification of an MR brain image using a fuzzy c-means algortihm. Bias field is modeled as a lower order polynomial. Bias field and tissue classification are estimated iteratively in an EM fashion. Internally, each voxel is assigned tissue membership function values, which range from 0 to 1. At any voxel, the sum of membership function of all classes is either 0 (outside of brain), or 1. The membership functions are converted in tissue labels to generate hard segmentation. | ||
== Usage == | == Usage == | ||
Revision as of 02:49, 29 April 2010
Home < Modules:FuzzySegmentationModuleReturn to Slicer 3.6 Documentation
Module Name
Fuzzy Tissue Classification
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General Information
Module Type & Category
Type: CLI
Category: Segmentation
Authors, Collaborators & Contact
- Author: Xiaodong Tao
- Contact: taox at research.ge.com
Module Description
This module computes voxel by voxel tissue classification of an MR brain image using a fuzzy c-means algortihm. Bias field is modeled as a lower order polynomial. Bias field and tissue classification are estimated iteratively in an EM fashion. Internally, each voxel is assigned tissue membership function values, which range from 0 to 1. At any voxel, the sum of membership function of all classes is either 0 (outside of brain), or 1. The membership functions are converted in tissue labels to generate hard segmentation.
Usage
Examples, Use Cases & Tutorials
Quick Tour of Features and Use
Development
Dependencies
Known bugs
None.
Usability issues
None.
Source code & documentation
Source Code:
XML Description:
Usage:
