{"title":"从眼底图像中自动提取视盘区域用于眼周前青光眼诊断","authors":"Ji Sang Park, H. Cho, J. Cho","doi":"10.23919/ICCAS.2017.8204381","DOIUrl":null,"url":null,"abstract":"This paper presents an automated technique to detect optical disc (OD) regions and to locate clipping circles to separate OD and non-OD regions using fundus images. After surveys on different OD detection techniques, a set of image and geometric processing techniques is selected and implemented. Several public fundus images with different ophthalmologic diseases are used to experiment and to verify the performance of the proposed algorithm. The proposed algorithm tends to locate clipping circles properly by enclosing OD regions with fundus images of healthy patients. However, the algorithm is not good enough to process fundus images of different ophthalmologic conditions. The overall performance of the proposed algorithm is discussed along with several experimental results. Several future research issues are also addressed.","PeriodicalId":140598,"journal":{"name":"2017 17th International Conference on Control, Automation and Systems (ICCAS)","volume":"294 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Automated extraction of optic disc regions from fundus images for preperimetric glaucoma diagnosis\",\"authors\":\"Ji Sang Park, H. Cho, J. Cho\",\"doi\":\"10.23919/ICCAS.2017.8204381\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an automated technique to detect optical disc (OD) regions and to locate clipping circles to separate OD and non-OD regions using fundus images. After surveys on different OD detection techniques, a set of image and geometric processing techniques is selected and implemented. Several public fundus images with different ophthalmologic diseases are used to experiment and to verify the performance of the proposed algorithm. The proposed algorithm tends to locate clipping circles properly by enclosing OD regions with fundus images of healthy patients. However, the algorithm is not good enough to process fundus images of different ophthalmologic conditions. The overall performance of the proposed algorithm is discussed along with several experimental results. Several future research issues are also addressed.\",\"PeriodicalId\":140598,\"journal\":{\"name\":\"2017 17th International Conference on Control, Automation and Systems (ICCAS)\",\"volume\":\"294 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 17th International Conference on Control, Automation and Systems (ICCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ICCAS.2017.8204381\",\"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 17th International Conference on Control, Automation and Systems (ICCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ICCAS.2017.8204381","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automated extraction of optic disc regions from fundus images for preperimetric glaucoma diagnosis
This paper presents an automated technique to detect optical disc (OD) regions and to locate clipping circles to separate OD and non-OD regions using fundus images. After surveys on different OD detection techniques, a set of image and geometric processing techniques is selected and implemented. Several public fundus images with different ophthalmologic diseases are used to experiment and to verify the performance of the proposed algorithm. The proposed algorithm tends to locate clipping circles properly by enclosing OD regions with fundus images of healthy patients. However, the algorithm is not good enough to process fundus images of different ophthalmologic conditions. The overall performance of the proposed algorithm is discussed along with several experimental results. Several future research issues are also addressed.