直觉鲁棒聚类用于皮肤镜图像中的病变分割

IF 0.8 4区工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY

Dyna Pub Date : 2024-01-01 DOI:10.6036/10787

Celia RAMOS PALENCIA, Dante Mújica Vargas, Jean Marie Vianney KINANI KINANI, Antonio LUNA ALVAREZ, Noé Alejandro Castro Sánchez

{"title":"直觉鲁棒聚类用于皮肤镜图像中的病变分割","authors":"Celia RAMOS PALENCIA, Dante Mújica Vargas, Jean Marie Vianney KINANI KINANI, Antonio LUNA ALVAREZ, Noé Alejandro Castro Sánchez","doi":"10.6036/10787","DOIUrl":null,"url":null,"abstract":"This paper presents the formulation of the intuitive fuzzy clustering algorithm to be robust to atypical data present in dermoscopic images and to delimit the affected area. This algorithm is formulated from the objective function derivation for memberships update, to integrate an m-redescending estimator influence function. Experimentation shows an accuracy of 95% with the proposal algorithm with respect to other clustering algorithms to perform delimitations, in addition the iterations number is considerably reduced.\nKeywords: Robust Intuitionistic Fuzzy Clustering, Dermoscopic Images, Delimitations of Lesions, M-redescending Estimator","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"1 9","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"INTUITIONISTIC ROBUST CLUSTERING FOR SEGMENTATION OF LESIONS IN DERMATOSCOPIC IMAGES\",\"authors\":\"Celia RAMOS PALENCIA, Dante Mújica Vargas, Jean Marie Vianney KINANI KINANI, Antonio LUNA ALVAREZ, Noé Alejandro Castro Sánchez\",\"doi\":\"10.6036/10787\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the formulation of the intuitive fuzzy clustering algorithm to be robust to atypical data present in dermoscopic images and to delimit the affected area. This algorithm is formulated from the objective function derivation for memberships update, to integrate an m-redescending estimator influence function. Experimentation shows an accuracy of 95% with the proposal algorithm with respect to other clustering algorithms to perform delimitations, in addition the iterations number is considerably reduced.\\nKeywords: Robust Intuitionistic Fuzzy Clustering, Dermoscopic Images, Delimitations of Lesions, M-redescending Estimator\",\"PeriodicalId\":11386,\"journal\":{\"name\":\"Dyna\",\"volume\":\"1 9\",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Dyna\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.6036/10787\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dyna","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.6036/10787","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

摘要

本文提出了一种直观模糊聚类算法，该算法对皮肤镜图像中出现的非典型数据具有鲁棒性，并能划定受影响的区域。该算法从成员更新的目标函数推导出发，整合了一个 m 递减估计影响函数。实验结果表明，与其他聚类算法相比，该建议算法的划定准确率达到 95%，此外，迭代次数也大大减少：鲁棒直觉模糊聚类、皮肤镜图像、病变划界、M-降序估计器

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

INTUITIONISTIC ROBUST CLUSTERING FOR SEGMENTATION OF LESIONS IN DERMATOSCOPIC IMAGES

This paper presents the formulation of the intuitive fuzzy clustering algorithm to be robust to atypical data present in dermoscopic images and to delimit the affected area. This algorithm is formulated from the objective function derivation for memberships update, to integrate an m-redescending estimator influence function. Experimentation shows an accuracy of 95% with the proposal algorithm with respect to other clustering algorithms to perform delimitations, in addition the iterations number is considerably reduced. Keywords: Robust Intuitionistic Fuzzy Clustering, Dermoscopic Images, Delimitations of Lesions, M-redescending Estimator

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Dyna 工程技术-工程：综合

CiteScore

1.00

自引率

10.00%

发文量

131

审稿时长

6-12 weeks

期刊介绍： Founded in 1926, DYNA is one of the journal of general engineering most influential and prestigious in the world, as it recognizes Clarivate Analytics. Included in Science Citation Index Expanded, its impact factor is published every year in Journal Citations Reports (JCR). It is the Official Body for Science and Technology of the Spanish Federation of Regional Associations of Engineers (FAIIE). Scientific journal agreed with AEIM (Spanish Association of Mechanical Engineering) In character Scientific-technical, it is the most appropriate way for communication between Multidisciplinary Engineers and for expressing their ideas and experience. DYNA publishes 6 issues per year: January, March, May, July, September and November.