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The proposed approach was applied on Liver CT images, and a thorough comparison between both methods was carried out. FCM-M provided better accuracy when compared to the traditional FCM-E, with an area under the ROC curve of 85.44% and 47.96%, respectively. In terms of statistical significant analysis, a twofold benefit was obtained from using the proposed approach: the performance of the image segmentation procedure was maintained, or even slightly increased in some situations, while the CPU processing time was significantly decreased. The advantages inherent to the proposed FCM-M pave the way to a whole new chain of fully automatic segmentation methods.<\/jats:p>","DOI":"10.3233\/idt-160266","type":"journal-article","created":{"date-parts":[[2016,7,12]],"date-time":"2016-07-12T12:44:25Z","timestamp":1468327465000},"page":"393-406","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Fuzzy C-Means based on Minkowski distance for liver CT image segmentation"],"prefix":"10.1177","volume":"10","author":[{"given":"Abder-Rahman","family":"Ali","sequence":"first","affiliation":[{"name":"Scientific Research Group in Egypt (SRGE), Egypt"}]},{"given":"Micael S.","family":"Couceiro","sequence":"additional","affiliation":[{"name":"Artificial Perception for Intelligent Systems and Robotics (AP4ISR), Institute of Systems and Robotics (ISR), University of Coimbra, Coimbra, Portugal"},{"name":"Ingeniarius, Lda., Mealhada, Portugal"}]},{"given":"Aboul Ella","family":"Hassanien","sequence":"additional","affiliation":[{"name":"Scientific Research Group in Egypt (SRGE), Egypt"},{"name":"Faculty of Computers and Information, Cairo University, Cairo, Egypt"}]},{"given":"D. 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