Multiobjective fuzzy clustering with coalition formation: the case of brain image processing. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Abdelaziz, Fouad Ben; Limam, Olfa
• Is Part Of: Infor. Volume 55:Issue 1(2017)
• Page Start: 52
• Page End: 69
• Publication Date: 2017-01-02
• Subjects: Multi-objective fuzzy clustering -- Shapley measure -- iterative model -- MR brain image; Operations research -- Periodicals; Electronic data processing -- Periodicals; Systems engineering -- Periodicals; Systems engineering; Electronic data processing; Periodicals; 003.05
• DOI: 10.1080/03155986.2016.1262582
• Languages: English
• ISSNs: 0315-5986

Abstract

ABSTRACT: 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.