{"title":"OD-Match:基于PatchMatch的光盘检测","authors":"S. Ramakanth, R. Venkatesh Babu","doi":"10.1109/NCVPRIPG.2013.6776206","DOIUrl":null,"url":null,"abstract":"Approximate Nearest-Neighbour Field has been an area of interest in recent research for a wide variety of topics in graphics and multimedia community. Medical image processing is a relatively unaffected field by these developments in ANNF computations, brought about by various extremely efficient algorithms like PatchMatch. In this paper, we use Generalized PatchMatch for Optic Disk detection, in retinal images, and show that by making use of efficient ANNF computations we are able to generate results with 98% accuracy with an average time of 0.5 sec. This is significantly faster than conventional Optic Disk detection methods, which average at 95-97% accuracy with 3-5 sec average computation time.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"OD-Match: PatchMatch based Optic Disk detection\",\"authors\":\"S. Ramakanth, R. Venkatesh Babu\",\"doi\":\"10.1109/NCVPRIPG.2013.6776206\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Approximate Nearest-Neighbour Field has been an area of interest in recent research for a wide variety of topics in graphics and multimedia community. Medical image processing is a relatively unaffected field by these developments in ANNF computations, brought about by various extremely efficient algorithms like PatchMatch. In this paper, we use Generalized PatchMatch for Optic Disk detection, in retinal images, and show that by making use of efficient ANNF computations we are able to generate results with 98% accuracy with an average time of 0.5 sec. This is significantly faster than conventional Optic Disk detection methods, which average at 95-97% accuracy with 3-5 sec average computation time.\",\"PeriodicalId\":436402,\"journal\":{\"name\":\"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCVPRIPG.2013.6776206\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCVPRIPG.2013.6776206","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Approximate Nearest-Neighbour Field has been an area of interest in recent research for a wide variety of topics in graphics and multimedia community. Medical image processing is a relatively unaffected field by these developments in ANNF computations, brought about by various extremely efficient algorithms like PatchMatch. In this paper, we use Generalized PatchMatch for Optic Disk detection, in retinal images, and show that by making use of efficient ANNF computations we are able to generate results with 98% accuracy with an average time of 0.5 sec. This is significantly faster than conventional Optic Disk detection methods, which average at 95-97% accuracy with 3-5 sec average computation time.