{"title":"一种新的基于临床数据映射的白内障检测算法","authors":"Shashwat Pathak, Shubham Gupta, B. Kumar","doi":"10.1109/R10-HTC.2016.7906816","DOIUrl":null,"url":null,"abstract":"This paper proposes and evaluates an algorithm to automatically detect the cataracts from color images. Currently, methods available for cataract detection are based on the use of either fundus camera or DSLR camera; both are very expensive. The main motive behind this work is to develop an inexpensive, robust and convenient algorithm which in conjugation with suitable devices will be able to diagnose the presence of cataract from the true color images of eye. An algorithm is proposed for Cataract Screening based on texture features: uniformity, intensity and standard deviation. These features are first computed and mapped with diagnostic opinion by the eye expert to define the basic threshold of screening system later tested on real subjects in eye clinic.","PeriodicalId":174678,"journal":{"name":"2016 IEEE Region 10 Humanitarian Technology Conference (R10-HTC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A novel cataract detection algorithm using clinical data mapping\",\"authors\":\"Shashwat Pathak, Shubham Gupta, B. Kumar\",\"doi\":\"10.1109/R10-HTC.2016.7906816\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes and evaluates an algorithm to automatically detect the cataracts from color images. Currently, methods available for cataract detection are based on the use of either fundus camera or DSLR camera; both are very expensive. The main motive behind this work is to develop an inexpensive, robust and convenient algorithm which in conjugation with suitable devices will be able to diagnose the presence of cataract from the true color images of eye. An algorithm is proposed for Cataract Screening based on texture features: uniformity, intensity and standard deviation. These features are first computed and mapped with diagnostic opinion by the eye expert to define the basic threshold of screening system later tested on real subjects in eye clinic.\",\"PeriodicalId\":174678,\"journal\":{\"name\":\"2016 IEEE Region 10 Humanitarian Technology Conference (R10-HTC)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Region 10 Humanitarian Technology Conference (R10-HTC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/R10-HTC.2016.7906816\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Region 10 Humanitarian Technology Conference (R10-HTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/R10-HTC.2016.7906816","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel cataract detection algorithm using clinical data mapping
This paper proposes and evaluates an algorithm to automatically detect the cataracts from color images. Currently, methods available for cataract detection are based on the use of either fundus camera or DSLR camera; both are very expensive. The main motive behind this work is to develop an inexpensive, robust and convenient algorithm which in conjugation with suitable devices will be able to diagnose the presence of cataract from the true color images of eye. An algorithm is proposed for Cataract Screening based on texture features: uniformity, intensity and standard deviation. These features are first computed and mapped with diagnostic opinion by the eye expert to define the basic threshold of screening system later tested on real subjects in eye clinic.