An Effective Possibilistic Fuzzy Clustering Method for Tumor Segmentation in MRI brain Images

B. Saravanan, M. Duraipandian, V. Pandiaraj
{"title":"An Effective Possibilistic Fuzzy Clustering Method for Tumor Segmentation in MRI brain Images","authors":"B. Saravanan, M. Duraipandian, V. Pandiaraj","doi":"10.1109/I-SMAC55078.2022.9987388","DOIUrl":null,"url":null,"abstract":"The segmentation of tumors in magnetic resonance imaging (MRI) is a medical emergency operation. Weakened MR images of the brain are used to segment them using the fuzzy C-means (FCM) clustering technique. The run time is longer because of the need to continuously calculate the clustering parameters. Using the probabilistic fuzzy clustering (PFC) technique for brain MRI image segmentation is recommended by the authors of this article. Morphological reconstruction and computation of local spatial similarity factors are performed before commencing the clustering step. Integrating a local spatial similarity factor into the morphological reconstruction process reduces noise, while maintaining the information's structural integrity.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I-SMAC55078.2022.9987388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The segmentation of tumors in magnetic resonance imaging (MRI) is a medical emergency operation. Weakened MR images of the brain are used to segment them using the fuzzy C-means (FCM) clustering technique. The run time is longer because of the need to continuously calculate the clustering parameters. Using the probabilistic fuzzy clustering (PFC) technique for brain MRI image segmentation is recommended by the authors of this article. Morphological reconstruction and computation of local spatial similarity factors are performed before commencing the clustering step. Integrating a local spatial similarity factor into the morphological reconstruction process reduces noise, while maintaining the information's structural integrity.
一种有效的磁共振脑图像肿瘤分割的可能性模糊聚类方法
核磁共振成像(MRI)中的肿瘤分割是一种医学紧急手术。使用模糊c均值(FCM)聚类技术对减弱的脑磁共振图像进行分割。运行时间较长,因为需要不断地计算集群参数。本文推荐使用概率模糊聚类(PFC)技术进行脑MRI图像分割。在开始聚类步骤之前,进行形态重建和局部空间相似因子的计算。在形态学重构过程中引入局部空间相似性因子,在保持信息结构完整性的同时降低了噪声。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信