18 January 2004 Possibilistic-clustering-based MR brain image segmentation with accurate initialization
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Abstract
Magnetic resonance image analysis by computer is useful to aid diagnosis of malady. We present in this paper a automatic segmentation method for principal brain tissues. It is based on the possibilistic clustering approach, which is an improved fuzzy c-means clustering method. In order to improve the efficiency of clustering process, the initial value problem is discussed and solved by combining with a histogram analysis method. Our method can automatically determine number of classes to cluster and the initial values for each class. It has been tested on a set of forty MR brain images with or without the presence of tumor. The experimental results showed that it is simple, rapid and robust to segment the principal brain tissues.
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Qingmin Liao, Yingying Deng, Weibei Dou, Su Ruan, Daniel Bloyet, "Possibilistic-clustering-based MR brain image segmentation with accurate initialization", Proc. SPIE 5308, Visual Communications and Image Processing 2004, (18 January 2004); doi: 10.1117/12.526800; https://doi.org/10.1117/12.526800
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