Author(s)

Zhuang Miao, Xiaomei Lin, Chengcheng Liu

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In medical images, exist often a lot of noise, the noise will seriously affect the accuracy of the segmentation results. The traditional standard fuzzy c-means(FCM) algorithm in image segmentation do not taken into account the relationship the adjacent pixels, which leads to the standard fuzzy c-means(FCM) algorithm is very sensitive to noise in the image. Proposed improvedfuzzy c-means(FCM) algorithm, taking both the local and non-local information into the standard fuzzy c-means(FCM) clustering algorithm. The ex-periment results can show that the improved algorithm can achieve better effect than other methods of brain tissue segmentation.

Local Information; Non-local Mean; Brain Tissue Segmentation

Miao, Z. , Lin, X. and Liu, C. (2011) Automatic segmentation of brain tissue based on improvedfuzzy c means clustering algorithm. Journal of Biomedical Science and Engineering, 4, 100-104. doi: 10.4236/jbise.2011.42014.