A novel fuzzy Dempster-Shafer inference system for brain MRI segmentation
Information Sciences: an International Journal
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This paper presents a robust automatic threshold finding method for the human brain MR image segmentation. The method is based on fuzzy information granulation shown by Zadeh. The human brain MR image consists of several parts; the gray matter, white matter, cerebrospinal fluid and so on. By treating their parts as the fuzzy granules in the gray level histogram of the image and developing fuzzy matching technique, we can find required thresholds and can segment the brain region from the MR image. An experiment is done on 50 gray level histograms of the human brain MR volumes. To evaluate our method, we extract the brain region using the obtained thresholds. A comparison of the obtained region with canonical atlas images shows that our method find the thresholds of the gray matter and white matter correctly.