Feature ranking-guided fuzzy rule interpolation for mammographic mass shape classification

Fangyi Li, Changjing Shang, Ying Li, Qiang Shen

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

This paper presents a novel fuzzy rule-based interpolative reasoning system for mammographic mass shape classification that is interpretable to medical professionals. In particular, a feature ranking-guided fuzzy rule interpolation (FRI) method is embedded in the proposed system to make inference possible given a sparse rule base, which may occur in dealing with insufficient mammographic image data (and indeed in coping with many other computer-aided medical diagnostic problems). The rule base for inference is learned from a set of labelled morphological features which are extracted from mass shapes. A classical FRI mechanism is integrated with a procedure for feature selection to score the individual rule antecedents in the inducted sparse rule base for more accurate interpolative reasoning. The work is evaluated on a real-world mammographic image data base with promising results, demonstrating the efficacy of the proposed fuzzy rule-based interpolative classification system.

源语言英语
主期刊名2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018 - Proceedings
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9781509060207
DOI
出版状态已出版 - 12 10月 2018
活动2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018 - Rio de Janeiro, 巴西
期限: 8 7月 201813 7月 2018

出版系列

姓名IEEE International Conference on Fuzzy Systems
2018-July
ISSN(印刷版)1098-7584

会议

会议2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018
国家/地区巴西
Rio de Janeiro
时期8/07/1813/07/18

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