Wbc Image Segmentation Using Modified Fuzzy Possibilistic C - Means Algorithm

Medical Image Segmentation becomes vital process for its proper detection and diagnosis of diseases. In which accurate White Blood Cells segmentation becomes important issue because differential counting, plays a major role in the determination the diseases and based on it the treatment is followed for the patients. To address this work here various fuzzy based clustering techniques are proposed. Already known that Clustering plays a major role for its further process and reduced results will affect its further classification or other processes. The Standard Fuzzy C Means and Standard Fuzzy Possibilistic C Means are modified and its performance is evaluated by various measures and proved as a successful technique.