Segmentation for the magnetic resonance images of Covid-19 patients using adaptive automatic Kernel-Based fuzzy clustering algorithm

T. Vovan, D. Phamtoan
{"title":"Segmentation for the magnetic resonance images of Covid-19 patients using adaptive automatic Kernel-Based fuzzy clustering algorithm","authors":"T. Vovan, D. Phamtoan","doi":"10.1063/5.0066463","DOIUrl":null,"url":null,"abstract":"This paper proposes the segment method for the Magnetic Resonance Images (MRI) of Covid-19 patients using the adaptive automatic Kernel-Based fuzzy clustering algorithm. This method not only finds the suitable number of clusters but also builds fuzzy clusters via the improvement from the Kernel-Based fuzzy clustering algorithm. Moreover, the algorithm uses the grayscale of the average filter in order to replace the local average ones. The outstanding advantages of this method are the adaptive ability of the average filter, increasing the intensity of image details, independence of separative groups, and decreasing computational costs. In addition, the experimental results also show the potential of the developed model. The algorithm is effectively performed by the established Matlab procedure. © 2021 Author(s).","PeriodicalId":253890,"journal":{"name":"1ST VAN LANG INTERNATIONAL CONFERENCE ON HERITAGE AND TECHNOLOGY CONFERENCE PROCEEDING, 2021: VanLang-HeriTech, 2021","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1ST VAN LANG INTERNATIONAL CONFERENCE ON HERITAGE AND TECHNOLOGY CONFERENCE PROCEEDING, 2021: VanLang-HeriTech, 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1063/5.0066463","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This paper proposes the segment method for the Magnetic Resonance Images (MRI) of Covid-19 patients using the adaptive automatic Kernel-Based fuzzy clustering algorithm. This method not only finds the suitable number of clusters but also builds fuzzy clusters via the improvement from the Kernel-Based fuzzy clustering algorithm. Moreover, the algorithm uses the grayscale of the average filter in order to replace the local average ones. The outstanding advantages of this method are the adaptive ability of the average filter, increasing the intensity of image details, independence of separative groups, and decreasing computational costs. In addition, the experimental results also show the potential of the developed model. The algorithm is effectively performed by the established Matlab procedure. © 2021 Author(s).
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
基于自适应自动核模糊聚类算法对新冠肺炎患者磁共振图像进行分割
本文提出了一种基于自适应自动核模糊聚类算法的新冠肺炎患者磁共振图像分割方法。该方法通过对基于核的模糊聚类算法的改进,找到了合适的聚类数量,并构建了模糊聚类。此外,该算法利用平均滤波器的灰度值来代替局部平均滤波器。该方法的突出优点是平均滤波器的自适应能力强,增强了图像细节的强度,分离组的独立性强,降低了计算成本。此外,实验结果也显示了所建立模型的潜力。该算法通过建立的Matlab程序有效地执行。©2021作者。
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
Optimizing the benefits of housing roofers in Ho Chi Minh City to adapt to the current climate change context Vegan leather: An eco-friendly material for sustainable fashion towards environmental awareness Power energy generation fuel cost optimization for thermal power plants using different type of fuels Resolving conflict between conservation and promotion heritage of urban architecture in Vietnam (Case study: Hanoi, Dalat, saigon - ho chi minh city) Urban art environment improvement in Ho Chi Minh City
×
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