Blotch Detection in Pigmented Skin Lesions Using Fuzzy Co-clustering and Texture Segmentation

V. Madasu, B. Lovell
{"title":"Blotch Detection in Pigmented Skin Lesions Using Fuzzy Co-clustering and Texture Segmentation","authors":"V. Madasu, B. Lovell","doi":"10.1109/DICTA.2009.15","DOIUrl":null,"url":null,"abstract":"The ‘Fuzzy Co-Clustering Algorithm for Images (FCCI)’ technique has been successfully applied to colour segmentation of medical images. The goal of this work is to extend this technique by the inclusion of texture features as a clustering parameter for detecting blotches in skin lesions based on colour information. The objective function is optimized using the bacterial foraging algorithm which gives image specific values to the parameters involved in the algorithm. Experiments show the efficacy of the proposed method in extracting malignant blotches from different types of pigmented skin lesion images.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Digital Image Computing: Techniques and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA.2009.15","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26

Abstract

The ‘Fuzzy Co-Clustering Algorithm for Images (FCCI)’ technique has been successfully applied to colour segmentation of medical images. The goal of this work is to extend this technique by the inclusion of texture features as a clustering parameter for detecting blotches in skin lesions based on colour information. The objective function is optimized using the bacterial foraging algorithm which gives image specific values to the parameters involved in the algorithm. Experiments show the efficacy of the proposed method in extracting malignant blotches from different types of pigmented skin lesion images.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于模糊共聚类和纹理分割的色斑检测
“图像模糊共聚类算法(FCCI)”技术已成功地应用于医学图像的颜色分割。这项工作的目标是通过包含纹理特征作为基于颜色信息检测皮肤病变中的斑点的聚类参数来扩展该技术。利用细菌觅食算法对目标函数进行优化,该算法为算法所涉及的参数提供图像特定值。实验结果表明,该方法能够有效地从不同类型的色素皮肤病变图像中提取出恶性斑点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Video Surveillance: Legally Blind? Mixed Pixel Analysis for Flood Mapping Using Extended Support Vector Machine 3D Reconstruction of Patient Specific Bone Models from 2D Radiographs for Image Guided Orthopedic Surgery Improved Single Image Dehazing Using Geometry Crowd Counting Using Multiple Local Features
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1