{"title":"基于皮质等高线映射的脑图像配准","authors":"C. Davatzikos, Jerry L Prince, R. Bryan","doi":"10.1109/NSSMIC.1993.373607","DOIUrl":null,"url":null,"abstract":"The authors address the problem of brain image registration, and they present a new, nonlinear registration technique. In the first step of the authors' technique they obtain a point-to-point mapping between the outer cortical contours of the brain images using an elastic string algorithm. In the second step the authors register the two images based on the point-to-point correspondence established in the first step. They propose a new, nonlinear registration transformation, which is based on a spatially variable scaling and relation that can describe highly nonlinear deformations. Finally, the authors test their algorithm on two different registration problems: they first consider the registration of a postmortem photograph of a baboon brain cross-section and then an MR image of approximately the same cross-section.<<ETX>>","PeriodicalId":287813,"journal":{"name":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Brain image registration based on cortical contour mapping\",\"authors\":\"C. Davatzikos, Jerry L Prince, R. Bryan\",\"doi\":\"10.1109/NSSMIC.1993.373607\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors address the problem of brain image registration, and they present a new, nonlinear registration technique. In the first step of the authors' technique they obtain a point-to-point mapping between the outer cortical contours of the brain images using an elastic string algorithm. In the second step the authors register the two images based on the point-to-point correspondence established in the first step. They propose a new, nonlinear registration transformation, which is based on a spatially variable scaling and relation that can describe highly nonlinear deformations. Finally, the authors test their algorithm on two different registration problems: they first consider the registration of a postmortem photograph of a baboon brain cross-section and then an MR image of approximately the same cross-section.<<ETX>>\",\"PeriodicalId\":287813,\"journal\":{\"name\":\"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NSSMIC.1993.373607\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NSSMIC.1993.373607","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Brain image registration based on cortical contour mapping
The authors address the problem of brain image registration, and they present a new, nonlinear registration technique. In the first step of the authors' technique they obtain a point-to-point mapping between the outer cortical contours of the brain images using an elastic string algorithm. In the second step the authors register the two images based on the point-to-point correspondence established in the first step. They propose a new, nonlinear registration transformation, which is based on a spatially variable scaling and relation that can describe highly nonlinear deformations. Finally, the authors test their algorithm on two different registration problems: they first consider the registration of a postmortem photograph of a baboon brain cross-section and then an MR image of approximately the same cross-section.<>