Yan Cao, Michael I Miller, Susumu Mori, Raimond L Winslow, Laurent Younes
{"title":"Diffeomorphic Matching of Diffusion Tensor Images.","authors":"Yan Cao, Michael I Miller, Susumu Mori, Raimond L Winslow, Laurent Younes","doi":"10.1109/CVPRW.2006.65","DOIUrl":null,"url":null,"abstract":"<p><p>This paper proposes a method to match diffusion tensor magnetic resonance images (DT-MRI) through the large deformation diffeomorphic metric mapping of tensor fields on the image volume, resulting in optimizing for geodesics on the space of diffeomorphisms connecting two diffusion tensor images. A coarse to fine multi-resolution and multi-kernel-width scheme is detailed, to reduce both ambiguities and computation load. This is illustrated by numerical experiments on DT-MRI brain and images.</p>","PeriodicalId":74560,"journal":{"name":"Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"2006 ","pages":"67"},"PeriodicalIF":0.0000,"publicationDate":"2006-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2920614/pdf/nihms189851.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPRW.2006.65","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
This paper proposes a method to match diffusion tensor magnetic resonance images (DT-MRI) through the large deformation diffeomorphic metric mapping of tensor fields on the image volume, resulting in optimizing for geodesics on the space of diffeomorphisms connecting two diffusion tensor images. A coarse to fine multi-resolution and multi-kernel-width scheme is detailed, to reduce both ambiguities and computation load. This is illustrated by numerical experiments on DT-MRI brain and images.