Multiobjective fuzzy clustering with coalition formation: the case of brain image processing

This paper presents a multi-objective fuzzy clustering approach under iterative modelling for the segmentation of human brain multispectral magnetic resonance image. It optimizes the global spatial fuzzy compactness and fuzzy spatial separation among clusters. Our method generates an ensemble of Pareto solutions among which the final solution will be proposed to the analyst. At this final step, the Shapley value concept is utilized to select the best solution. An empirical study on brain images shows a better performance of our proposed method when compared to competing algorithms.