Rough Set based MRI Medical image segmentation using optimized initial centroids
نویسندگان
چکیده
Medical image segmentation plays a vital role in image processing due to the catering needs of the medical images in automating, delineating anatomical structures and diagnosis. Very often the medical images contain uncertain, vague, and incomplete data definition. The concepts of lower and upper approximations of rough sets effectively handle this data. In this paper, rough sets based clustering is analyzed with respect to Kmeans and Fuzzy C-means algorithms for MRI images of BrainWeb database and the centroids are optimized using local maxima of histogram. The performance of proposed Rough K-means(RKM) and Rough Fuzzy Cmeans (RFCM) is evaluated and compared with classic k-means (KM) and fuzzy C-means (FCM)
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