一种改进的MRI图像序列心脏边界识别与跟踪方法

B. Chaudhuri, A. Bhattacharya, S. Mitra, S. Dutta
{"title":"一种改进的MRI图像序列心脏边界识别与跟踪方法","authors":"B. Chaudhuri, A. Bhattacharya, S. Mitra, S. Dutta","doi":"10.1109/TENCON.2008.4766462","DOIUrl":null,"url":null,"abstract":"In the present work, a robust algorithm for automatic identification and segmentation of heart portion from cardiac Magnetic Resonance video Image (MRI) is presented. At first, an outline has been generated to get the region of interest (ROI) by employing the moving object criterion, which eventually reduces the processing time significantly. In the next step, Expectation Maximization (EM) algorithm is used to segment the grey scale images into 5 distinct regions. This is done to make them more suitable for further processing and easy to use in the developed software. Finally Level set algorithm added with automatic contour generation module is used for tracking the exact heart boundary to segment it out from the rest of the image. This algorithm gives equally persistent result for both long axis and shot axis cardiac MRI data consisting of a movie (in AVI format) containing 32 separate frames of grayscale images.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A modified approach of identification and tracking of heart boundary from MRI image sequences\",\"authors\":\"B. Chaudhuri, A. Bhattacharya, S. Mitra, S. Dutta\",\"doi\":\"10.1109/TENCON.2008.4766462\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the present work, a robust algorithm for automatic identification and segmentation of heart portion from cardiac Magnetic Resonance video Image (MRI) is presented. At first, an outline has been generated to get the region of interest (ROI) by employing the moving object criterion, which eventually reduces the processing time significantly. In the next step, Expectation Maximization (EM) algorithm is used to segment the grey scale images into 5 distinct regions. This is done to make them more suitable for further processing and easy to use in the developed software. Finally Level set algorithm added with automatic contour generation module is used for tracking the exact heart boundary to segment it out from the rest of the image. This algorithm gives equally persistent result for both long axis and shot axis cardiac MRI data consisting of a movie (in AVI format) containing 32 separate frames of grayscale images.\",\"PeriodicalId\":22230,\"journal\":{\"name\":\"TENCON 2008 - 2008 IEEE Region 10 Conference\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"TENCON 2008 - 2008 IEEE Region 10 Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TENCON.2008.4766462\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"TENCON 2008 - 2008 IEEE Region 10 Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TENCON.2008.4766462","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文提出了一种鲁棒的心脏磁共振视频图像自动识别和分割算法。首先利用运动目标准则生成轮廓,得到感兴趣区域(ROI),从而大大缩短了处理时间。下一步,使用期望最大化算法将灰度图像分割成5个不同的区域。这样做是为了使它们更适合进一步加工,并且易于在开发的软件中使用。最后利用添加了自动轮廓生成模块的水平集算法跟踪精确的心脏边界,将其从图像中分割出来。对于包含32帧灰度图像的电影(AVI格式)组成的长轴和短轴心脏MRI数据,该算法给出了同样持久的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A modified approach of identification and tracking of heart boundary from MRI image sequences
In the present work, a robust algorithm for automatic identification and segmentation of heart portion from cardiac Magnetic Resonance video Image (MRI) is presented. At first, an outline has been generated to get the region of interest (ROI) by employing the moving object criterion, which eventually reduces the processing time significantly. In the next step, Expectation Maximization (EM) algorithm is used to segment the grey scale images into 5 distinct regions. This is done to make them more suitable for further processing and easy to use in the developed software. Finally Level set algorithm added with automatic contour generation module is used for tracking the exact heart boundary to segment it out from the rest of the image. This algorithm gives equally persistent result for both long axis and shot axis cardiac MRI data consisting of a movie (in AVI format) containing 32 separate frames of grayscale images.
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
×
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