Brain tumor segmentation using wavelet Multi-resolution expectation maximization algorithm

D. M. S. El-Torky, M. Al-Berry, M. A. Salem, Mohamed Roushdy
{"title":"Brain tumor segmentation using wavelet Multi-resolution expectation maximization algorithm","authors":"D. M. S. El-Torky, M. Al-Berry, M. A. Salem, Mohamed Roushdy","doi":"10.1109/INTELCIS.2017.8260030","DOIUrl":null,"url":null,"abstract":"Magnetic Resonance Imaging is one of the most important tools for diagnosing brain cancer. The variation in shape, size, location and structure of brain tumors makes it challenging for segmentation. Accurate brain tumor segmentation helps in taking accurate treatment decisions. In this paper, the Wavelet Multiresolution Expectation Maximization (WMEM) algorithm is explained and applied on brain MRI for tumor segmentation. The performance of the algorithm is evaluated using real Magnetic Resonance Imaging (MRI) images with segmented ground truth.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INTELCIS.2017.8260030","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

Magnetic Resonance Imaging is one of the most important tools for diagnosing brain cancer. The variation in shape, size, location and structure of brain tumors makes it challenging for segmentation. Accurate brain tumor segmentation helps in taking accurate treatment decisions. In this paper, the Wavelet Multiresolution Expectation Maximization (WMEM) algorithm is explained and applied on brain MRI for tumor segmentation. The performance of the algorithm is evaluated using real Magnetic Resonance Imaging (MRI) images with segmented ground truth.
基于小波多分辨率期望最大化算法的脑肿瘤分割
磁共振成像是诊断脑癌最重要的工具之一。脑肿瘤在形状、大小、位置和结构上的差异给分割带来了挑战。准确的脑肿瘤分割有助于做出准确的治疗决定。介绍了小波多分辨率期望最大化(WMEM)算法,并将其应用于脑MRI肿瘤分割。利用真实的磁共振成像(MRI)图像对算法的性能进行了评估。
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