MRI脑医学图像异常组织提取

D. Cherifi, M. Doghmane, A. Nait-Ali, Zakia Aici, Salim Bouzelha
{"title":"MRI脑医学图像异常组织提取","authors":"D. Cherifi, M. Doghmane, A. Nait-Ali, Zakia Aici, Salim Bouzelha","doi":"10.1109/WOSSPA.2011.5931510","DOIUrl":null,"url":null,"abstract":"This study is a comparison between two image segmentation's methods; the first method is based on normal brain's tissue recognition then tumor extraction using thresholding method. The second method is classification based on EM segmentation which is used for both brain recognition and tumor extraction. The goal of these methods is to detect, segment, extract, classify and measure properties of the brain normal and abnormal (tumor) tissues","PeriodicalId":343415,"journal":{"name":"International Workshop on Systems, Signal Processing and their Applications, WOSSPA","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Abnormal tissus extraction in MRI brain medical images\",\"authors\":\"D. Cherifi, M. Doghmane, A. Nait-Ali, Zakia Aici, Salim Bouzelha\",\"doi\":\"10.1109/WOSSPA.2011.5931510\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study is a comparison between two image segmentation's methods; the first method is based on normal brain's tissue recognition then tumor extraction using thresholding method. The second method is classification based on EM segmentation which is used for both brain recognition and tumor extraction. The goal of these methods is to detect, segment, extract, classify and measure properties of the brain normal and abnormal (tumor) tissues\",\"PeriodicalId\":343415,\"journal\":{\"name\":\"International Workshop on Systems, Signal Processing and their Applications, WOSSPA\",\"volume\":\"104 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on Systems, Signal Processing and their Applications, WOSSPA\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WOSSPA.2011.5931510\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Systems, Signal Processing and their Applications, WOSSPA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOSSPA.2011.5931510","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

摘要

本研究是对两种图像分割方法的比较;第一种方法是在正常脑组织识别的基础上,利用阈值法提取肿瘤。第二种方法是基于EM分割的分类,该方法用于脑识别和肿瘤提取。这些方法的目的是检测、分割、提取、分类和测量大脑正常和异常(肿瘤)组织的特性
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Abnormal tissus extraction in MRI brain medical images
This study is a comparison between two image segmentation's methods; the first method is based on normal brain's tissue recognition then tumor extraction using thresholding method. The second method is classification based on EM segmentation which is used for both brain recognition and tumor extraction. The goal of these methods is to detect, segment, extract, classify and measure properties of the brain normal and abnormal (tumor) tissues
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
自引率
0.00%
发文量
0
期刊最新文献
Performance limitations of an optical RZ-DPSK transmission system affected by frequency chirp, chromatic dispersion and polarization mode dispersion MPEG-4 AVC re-encoding for watermarking purposes Some issues on cognitive radio and UWB technology convergence for enabling green networks Adaptive blind equalization for QAM modulated signals in the presence of frequency offset Elliptic Curve Cryptography and its applications
×
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