{"title":"Registration of retinal images using adaptive adjacency graphs","authors":"P. Jasiobedzki","doi":"10.1109/CBMS.1993.262993","DOIUrl":null,"url":null,"abstract":"This paper presents a new method of retinal image registration. The method is based on representing a segmented reference image as an adaptive adjacency graph. The graph consists of a network of active contours, nodes where contours are connected, regions outlined by the contours and their full adjacency relationship. The contours in the graph correspond to retinal vessels or other curvilinear features. The registration is performed by placing the graph on the image to be registered and allowing it to adapt to the image data. The contours move under combined effect of internal and external forces. The internal forces represent contour internal energy. The external forces correspond to image data and to connectivity constraints imposed on the contours. Results of registration obtained for retinal images are presented.<<ETX>>","PeriodicalId":250310,"journal":{"name":"[1993] Computer-Based Medical Systems-Proceedings of the Sixth Annual IEEE Symposium","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1993] Computer-Based Medical Systems-Proceedings of the Sixth Annual IEEE Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.1993.262993","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
This paper presents a new method of retinal image registration. The method is based on representing a segmented reference image as an adaptive adjacency graph. The graph consists of a network of active contours, nodes where contours are connected, regions outlined by the contours and their full adjacency relationship. The contours in the graph correspond to retinal vessels or other curvilinear features. The registration is performed by placing the graph on the image to be registered and allowing it to adapt to the image data. The contours move under combined effect of internal and external forces. The internal forces represent contour internal energy. The external forces correspond to image data and to connectivity constraints imposed on the contours. Results of registration obtained for retinal images are presented.<>