Type-reduced vague possibilistic fuzzy clustering for medical images
作者：
Highlights：
• Effective hybridization of fuzzy and possibilistic membership to obtain an optimum solution.
• A vague environment is created using this hybridization.
• It takes probabilistic membership as the upper bound and possibilistic membership as the lower bound.
• Experimental results show the efficiency of the proposed work on the diagnosis of medical images.
• The novelty of the proposed approach is mentioned in terms of accuracy and error detection.
摘要
•Effective hybridization of fuzzy and possibilistic membership to obtain an optimum solution.•A vague environment is created using this hybridization.•It takes probabilistic membership as the upper bound and possibilistic membership as the lower bound.•Experimental results show the efficiency of the proposed work on the diagnosis of medical images.•The novelty of the proposed approach is mentioned in terms of accuracy and error detection.
论文关键词：Fuzzy membership,Typicality,Vague set,Type-reduction,Medical images
论文评审过程：Received 17 January 2020, Revised 18 October 2020, Accepted 8 December 2020, Available online 11 December 2020, Version of Record 17 December 2020.
论文官网地址：https://doi.org/10.1016/j.patcog.2020.107784
