1. A modified Fuzzy C-means algorithm with symmetry information for MR brain image segmentation
- Author
-
Alan Wee-Chung Liew and Surani Anuradha Jayasuriya
- Subjects
business.industry ,Computer science ,Fuzzy set ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Bilateral symmetry ,Image segmentation ,Brain tissue ,Fuzzy logic ,ComputingMethodologies_PATTERNRECOGNITION ,Robustness (computer science) ,Computer Science::Computer Vision and Pattern Recognition ,Segmentation ,Computer vision ,Artificial intelligence ,Image denoising ,business ,Algorithm - Abstract
In this paper, we present a novel modified Fuzzy C-means algorithm with symmetry information to reduce the effect of noise in brain tissue segmentation in magnetic resonance image (MRI). We integrate brain's bilateral symmetry into the conventional Fuzzy C-means (FCM) as an additional term. In experiments, some synthetic images, and both simulated and real brain images were used to investigate the robustness of the method against noise. Finally, the method was compared with the conventional FCM algorithm. Results show the viability of the approach and the preliminary investigation appears promising.
- Published
- 2013