S. G. Vázquez, Brais Cancela, N. Barreira, M. G. Penedo, M. Sáez
{"title":"视网膜图像动静脉比的自动计算:用最小路径进行动静脉分类","authors":"S. G. Vázquez, Brais Cancela, N. Barreira, M. G. Penedo, M. Sáez","doi":"10.1109/DICTA.2010.106","DOIUrl":null,"url":null,"abstract":"Abnormalities in the retinal vessel tree are associated with different pathologies. Usually, they affect arteries and veins differently. In this regard, the arteriovenous ratio(AVR) is a measure of retinal vessel caliber, widely used in medicine to study the influence of these irregularities in disease evolution. Hence, the development of an automatic tool for AVR computation as well as any other tool for diagnosis support need an objective, reliable and fast artery/vein classifier. This paper proposes a technique to improve the retinal vessel classification in an AVR computation framework. The proposed methodology combines a color clustering strategy and a vessel tracking procedure based on minimal path approaches. The tests performed with 58 images manually labeled by three experts show promising results.","PeriodicalId":246460,"journal":{"name":"2010 International Conference on Digital Image Computing: Techniques and Applications","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"54","resultStr":"{\"title\":\"On the Automatic Computation of the Arterio-Venous Ratio in Retinal Images: Using Minimal Paths for the Artery/Vein Classification\",\"authors\":\"S. G. Vázquez, Brais Cancela, N. Barreira, M. G. Penedo, M. Sáez\",\"doi\":\"10.1109/DICTA.2010.106\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abnormalities in the retinal vessel tree are associated with different pathologies. Usually, they affect arteries and veins differently. In this regard, the arteriovenous ratio(AVR) is a measure of retinal vessel caliber, widely used in medicine to study the influence of these irregularities in disease evolution. Hence, the development of an automatic tool for AVR computation as well as any other tool for diagnosis support need an objective, reliable and fast artery/vein classifier. This paper proposes a technique to improve the retinal vessel classification in an AVR computation framework. The proposed methodology combines a color clustering strategy and a vessel tracking procedure based on minimal path approaches. The tests performed with 58 images manually labeled by three experts show promising results.\",\"PeriodicalId\":246460,\"journal\":{\"name\":\"2010 International Conference on Digital Image Computing: Techniques and Applications\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"54\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Digital Image Computing: Techniques and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DICTA.2010.106\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Digital Image Computing: Techniques and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA.2010.106","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the Automatic Computation of the Arterio-Venous Ratio in Retinal Images: Using Minimal Paths for the Artery/Vein Classification
Abnormalities in the retinal vessel tree are associated with different pathologies. Usually, they affect arteries and veins differently. In this regard, the arteriovenous ratio(AVR) is a measure of retinal vessel caliber, widely used in medicine to study the influence of these irregularities in disease evolution. Hence, the development of an automatic tool for AVR computation as well as any other tool for diagnosis support need an objective, reliable and fast artery/vein classifier. This paper proposes a technique to improve the retinal vessel classification in an AVR computation framework. The proposed methodology combines a color clustering strategy and a vessel tracking procedure based on minimal path approaches. The tests performed with 58 images manually labeled by three experts show promising results.