Improved fuzzy clustering approach: Application to medical image MRI

Currently, the MRI brain image processing is a vast area of research, several methods and approaches have been used to segment these images (thresholding, region, contour, clustering). In this work, we propose a novel segmentation approach, which is based on fuzzy clustering and also it allows to combine cooperatively expectation maximization algorithms and possibilist c-means. To validate our approach, we have tested successfully on several databases of real images MRI. Thus, to show the performance of our method, we compared our results with different segmentation algorithms: k-means, fuzzy c-means, possibilist c-means and expectation maximization.

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