Bias Field Corrected Fuzzy C-Means

Estimates the illumination artifact in 2D (color) and 3D CT and MRI and segments into classes.
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Updated 3 Nov 2009

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This function segments (clusters) an image into object classes, and estimates and corrects for slow varying illumination artifacts. Estimates and corrects for bias field in 3D MRI, streak artifacts in CT, and illumination artifacts in color photos.

It's an implementation of the paper of M.N. Ahmed et. al. "A Modified Fuzzy C-Means Algorithm for Bias Field estimation and Segmentation of MRI Data" 2002, IEEE Transactions on medical imaging.
Only difference is added Gaussian regularization to the bias-field, (disable when sigma is set to zero).

See the screenshot.

The code is both available as matlab code and as c-coded mex file for speed.

For a 2D image the mex-file segmentation takes a few seconds, for a 512x512x512 volume it takes up to 1900s

Compile the c-code, and try the examples in the help

Please report bugs, successes and other helpful comment.

Cite As

Dirk-Jan Kroon (2024). Bias Field Corrected Fuzzy C-Means (https://www.mathworks.com/matlabcentral/fileexchange/25712-bias-field-corrected-fuzzy-c-means), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2009b
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
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Version Published Release Notes
1.1.0.0

Now uploaded also the testimage, updated the screen-shot, and gave some information about the time in 2D and 3D .

1.0.0.0