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An Improved Fuzzy C-means Algorithm for MR Brain Image Segmentation


Khalid Abdel wahab ali qora, Prof.Dr.E.A.Zanaty


Vol. 18  No. 4  pp. 54-57


Segmentation is an important aspect of medical image processing, where Clustering approach is widely used in biomedical applications. Brain image segmentation is one of the most important parts of clinical diagnostic tools.Fuzzy C- Means (FCM) algorithm proved to be superior over the other clustering approaches in terms of segmentation efficiency. But the major drawback of the FCM algorithm is the unknown number of clusters that assumed randomly. The effectiveness of the FCM algorithm in terms of Unknown number of clusters is improved by using metaheuristic algorithm to converges to the best number of clusters based on Xie-Beni validation index. In this paper, Xie-Beni index is used to choose the best number of clusters for FCM resulted after comparing all values of the index have been chosen using the metaheuristic algorithm which means the best segmentation result


metaheuristic swarm MRI segmentation fuzzy c-means Pso