Computer-aided diagnostic system for breast cancer detection based on optimized segmentation scheme and supervised algorithm

IF 1.7 4区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Automatika Pub Date : 2023-09-19 DOI:10.1080/00051144.2023.2244307
S. Balaji, T. Arunprasath, M. Pallikonda Rajasekaran, G. Vishnuvarthanan, K. Sindhuja
{"title":"Computer-aided diagnostic system for breast cancer detection based on optimized segmentation scheme and supervised algorithm","authors":"S. Balaji, T. Arunprasath, M. Pallikonda Rajasekaran, G. Vishnuvarthanan, K. Sindhuja","doi":"10.1080/00051144.2023.2244307","DOIUrl":null,"url":null,"abstract":"Breast cancer is a serious threat to the womankind and it leads the susceptible kinds of cancer for women. The mortality rates due to breast cancer increases every single year and the World Health Organization (WHO) aims to reduce the occurrence of breast cancer by at least 2.5% per year. The occurrence of breast cancer can be minimized only when periodical screening is carried out. Mammography is one of the effective screening procedure, which can effectively locate earlier signs of breast cancer. As an aid, this work aims to present a system for the breast cancer detection and classification. This work is segregated into four phases and all these phases aim to enhance the classification performance. The efficiency of the proposed work is evaluated against the state-of-the-art approaches and the proposed contribution to the medical science. The computer-aided diagnostic system (CADS) proves 98.2% accuracy, with minimal false positive and false negative rates in a reasonable period of time.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automatika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/00051144.2023.2244307","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Breast cancer is a serious threat to the womankind and it leads the susceptible kinds of cancer for women. The mortality rates due to breast cancer increases every single year and the World Health Organization (WHO) aims to reduce the occurrence of breast cancer by at least 2.5% per year. The occurrence of breast cancer can be minimized only when periodical screening is carried out. Mammography is one of the effective screening procedure, which can effectively locate earlier signs of breast cancer. As an aid, this work aims to present a system for the breast cancer detection and classification. This work is segregated into four phases and all these phases aim to enhance the classification performance. The efficiency of the proposed work is evaluated against the state-of-the-art approaches and the proposed contribution to the medical science. The computer-aided diagnostic system (CADS) proves 98.2% accuracy, with minimal false positive and false negative rates in a reasonable period of time.
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
基于优化分割方案和监督算法的乳腺癌计算机辅助诊断系统
乳腺癌是对女性的严重威胁,是女性易患的癌症之一。乳腺癌的死亡率每年都在增加,世界卫生组织(世卫组织)的目标是将乳腺癌的发病率每年至少降低2.5%。只有定期进行筛查,才能将乳腺癌的发病率降到最低。乳房x光检查是一种有效的筛查方法,可以有效地发现乳腺癌的早期迹象。作为辅助,本工作旨在提出一个乳腺癌的检测和分类系统。这项工作分为四个阶段,所有这些阶段都旨在提高分类性能。拟议工作的效率是根据最先进的方法和对医学科学的拟议贡献来评估的。计算机辅助诊断系统(CADS)的准确率为98.2%,在合理的时间内假阳性和假阴性率最低。
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
Automatika
Automatika AUTOMATION & CONTROL SYSTEMS-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
4.00
自引率
5.30%
发文量
65
审稿时长
4.5 months
期刊介绍: AUTOMATIKA – Journal for Control, Measurement, Electronics, Computing and Communications is an international scientific journal that publishes scientific and professional papers in the field of automatic control, robotics, measurements, electronics, computing, communications and related areas. Click here for full Focus & Scope. AUTOMATIKA is published since 1960, and since 1991 by KoREMA - Croatian Society for Communications, Computing, Electronics, Measurement and Control, Member of IMEKO and IFAC.
期刊最新文献
Quasi Z source direct matrix converter based K- to three-phase wind energy conversion system using maximum constant boost current control modulation technique An adaptive multistage intrusion detection and prevention system in software defined networking environment SwinVNETR: Swin V-net Transformer with non-local block for volumetric MRI Brain Tumor Segmentation Dynamic control method of construction cost based on fuzzy neural network Data augmentation using a 1D-CNN model with MFCC/MFMC features for speech emotion recognition
×
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