Robust Fuzzy Segmentation of Magnetic Resonance Images

Authors:
Dzung L. Pham
Affiliations:
-
Venue:
CBMS '01 Proceedings of the Fourteenth IEEE Symposium on Computer-Based Medical Systems
Year:
2001

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Abstract

Abstract: A new approach for robust segmentation of magnetic resonance images is described. The approach is derived from a generalization of the objective function used in Pham and Prince's Adaptive Fuzzy C-means algorithm (AFCM). Within the objective function, an additional constraint is placed on the membership functions that forces them to be spatially smooth. Minimization of this objective function results in an unsupervised fuzzy segmentation algorithm that is robust to both intensity inhomogeniety artifacts as well as noise and other artifacts. The efficacy of the algorithm is demonstrated on simulated magnetic resonance images.