基于gabor纹理特征的脑图谱构建

Arkane Khaminkure, Paramate Horkaew, J. Panyavaraporn
{"title":"基于gabor纹理特征的脑图谱构建","authors":"Arkane Khaminkure, Paramate Horkaew, J. Panyavaraporn","doi":"10.1109/JCSSE.2017.8025935","DOIUrl":null,"url":null,"abstract":"Brain atlas has become a primary means of computer aided neurological diagnosis. It relies on registering intra/inter-subject brain scans on a common frame of reference, on which statistical variability model is built. This diffeomorphic map of anatomically plausible correspondence could in turn be used for monitoring and identifying progress and manifestation of the disease, respectively. It is accepted that dense image registration is very accurate but computationally expensive. This paper thus presents a feature based image registration by using orientation invariant Gabor responses of texture. The reported results herein demonstrate that it is both anatomically accurate and robust.","PeriodicalId":6460,"journal":{"name":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"46 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Building a brain atlas based on gabor texture features\",\"authors\":\"Arkane Khaminkure, Paramate Horkaew, J. Panyavaraporn\",\"doi\":\"10.1109/JCSSE.2017.8025935\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Brain atlas has become a primary means of computer aided neurological diagnosis. It relies on registering intra/inter-subject brain scans on a common frame of reference, on which statistical variability model is built. This diffeomorphic map of anatomically plausible correspondence could in turn be used for monitoring and identifying progress and manifestation of the disease, respectively. It is accepted that dense image registration is very accurate but computationally expensive. This paper thus presents a feature based image registration by using orientation invariant Gabor responses of texture. The reported results herein demonstrate that it is both anatomically accurate and robust.\",\"PeriodicalId\":6460,\"journal\":{\"name\":\"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)\",\"volume\":\"46 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/JCSSE.2017.8025935\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/JCSSE.2017.8025935","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

脑图谱已成为计算机辅助神经学诊断的主要手段。它依赖于在一个共同的参考框架上记录主体内/主体间的大脑扫描,并在此基础上建立统计变异性模型。这种解剖上似是而非的对应的差胚图可以分别用于监测和识别疾病的进展和表现。人们普遍认为密集图像配准精度高,但计算量大。本文提出了一种基于纹理方向不变性Gabor响应的特征配准方法。本文报道的结果表明,它是解剖准确和稳健。
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
Building a brain atlas based on gabor texture features
Brain atlas has become a primary means of computer aided neurological diagnosis. It relies on registering intra/inter-subject brain scans on a common frame of reference, on which statistical variability model is built. This diffeomorphic map of anatomically plausible correspondence could in turn be used for monitoring and identifying progress and manifestation of the disease, respectively. It is accepted that dense image registration is very accurate but computationally expensive. This paper thus presents a feature based image registration by using orientation invariant Gabor responses of texture. The reported results herein demonstrate that it is both anatomically accurate and robust.
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
Isolate-Set-Based In-Memory Parallel Subgraph Matching Framework A Fast Attitude Estimation Method Using Homography Matrix IOT for smart farm: A case study of the Lingzhi mushroom farm at Maejo University Analyzing user reviews in Thai language toward aspects in mobile applications Front-rear crossover: A new crossover technique for solving a trap problem
×
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