基于灰度形态学的人类皮层MRI分割

R. Hult, E. Bengtsson
{"title":"基于灰度形态学的人类皮层MRI分割","authors":"R. Hult, E. Bengtsson","doi":"10.1109/ICIAP.2001.957072","DOIUrl":null,"url":null,"abstract":"An algorithm for fully automatic segmentation of the cortex from T1-weighted axial or sagittal MRI data is presented. When analysing 3D MRI images of the brain it is often important to segment the brain from non-brain tissue such as eyes and membranes of the brain. The segmentation algorithm uses a histogram-based method to find accurate threshold values. Four initial masks are created; first two thresholded masks from the original volume, background and brain tissue, then a third mask thresholded from a 3D grey-level eroded version of the volume, brain tissue, and lastly a fourth mask thresholded from a 3D grey-level dilated version of the volume, containing surrounding fat. On the start slice of these masks, binary morphological operations and logical operations are used. Then the rest of the slices are segmented using information from the previous slice combined with the other masks. Information from earlier slices is propagated to keep the segmented volume from leaking into non-brain tissue.","PeriodicalId":365627,"journal":{"name":"Proceedings 11th International Conference on Image Analysis and Processing","volume":"200 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Grey-level morphology based segmentation of MRI of the human cortex\",\"authors\":\"R. Hult, E. Bengtsson\",\"doi\":\"10.1109/ICIAP.2001.957072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An algorithm for fully automatic segmentation of the cortex from T1-weighted axial or sagittal MRI data is presented. When analysing 3D MRI images of the brain it is often important to segment the brain from non-brain tissue such as eyes and membranes of the brain. The segmentation algorithm uses a histogram-based method to find accurate threshold values. Four initial masks are created; first two thresholded masks from the original volume, background and brain tissue, then a third mask thresholded from a 3D grey-level eroded version of the volume, brain tissue, and lastly a fourth mask thresholded from a 3D grey-level dilated version of the volume, containing surrounding fat. On the start slice of these masks, binary morphological operations and logical operations are used. Then the rest of the slices are segmented using information from the previous slice combined with the other masks. Information from earlier slices is propagated to keep the segmented volume from leaking into non-brain tissue.\",\"PeriodicalId\":365627,\"journal\":{\"name\":\"Proceedings 11th International Conference on Image Analysis and Processing\",\"volume\":\"200 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 11th International Conference on Image Analysis and Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIAP.2001.957072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 11th International Conference on Image Analysis and Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIAP.2001.957072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

提出了一种从t1加权轴向或矢状面MRI数据中全自动分割皮层的算法。在分析大脑的3D MRI图像时,将大脑与非大脑组织(如眼睛和大脑膜)分割开来通常很重要。分割算法使用基于直方图的方法来找到准确的阈值。创建了四个初始掩码;首先是来自原始体积、背景和脑组织的两个阈值掩模,然后是来自体积、脑组织的3D灰度侵蚀版本的第三个掩模阈值,最后是来自体积的3D灰度扩张版本的第四个掩模阈值,包含周围的脂肪。在这些掩码的起始切片上,使用了二进制形态运算和逻辑运算。然后使用来自前一片的信息与其他掩码结合对其余的切片进行分割。来自早期切片的信息被传播,以防止分割的体积泄漏到非脑组织。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Grey-level morphology based segmentation of MRI of the human cortex
An algorithm for fully automatic segmentation of the cortex from T1-weighted axial or sagittal MRI data is presented. When analysing 3D MRI images of the brain it is often important to segment the brain from non-brain tissue such as eyes and membranes of the brain. The segmentation algorithm uses a histogram-based method to find accurate threshold values. Four initial masks are created; first two thresholded masks from the original volume, background and brain tissue, then a third mask thresholded from a 3D grey-level eroded version of the volume, brain tissue, and lastly a fourth mask thresholded from a 3D grey-level dilated version of the volume, containing surrounding fat. On the start slice of these masks, binary morphological operations and logical operations are used. Then the rest of the slices are segmented using information from the previous slice combined with the other masks. Information from earlier slices is propagated to keep the segmented volume from leaking into non-brain tissue.
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