Parsa Moradi, Naghme Nazer, A. K. Ahmadi, H. Mohammadzade, Hasan Khojasteh Jafari
{"title":"发现虹膜图像中的信息区域以预测糖尿病","authors":"Parsa Moradi, Naghme Nazer, A. K. Ahmadi, H. Mohammadzade, Hasan Khojasteh Jafari","doi":"10.1109/ICBME.2018.8703564","DOIUrl":null,"url":null,"abstract":"Alternative medicine can be used to achieve the healing effects of the experimental medicine, it also can predict diseases and prevent them, but validity of them is unproven. Iridology is an alternative medicine that claims to predict tissue weaknesses in the body by looking at the iris. The main object of this paper is to validate the using of iridology to predict diabetes, to do so iris images of 106 diabetic patients and 124 healthy controls were obtained and evaluated. The designed method is completely automatic and independent of iridologists. Also a novel algorithm is developed to improve the efficiency by finding the best region of iris automatically. The results showed the accuracy of 91.8% in the best setting, which shows the effectiveness of the proposed method.","PeriodicalId":338286,"journal":{"name":"2018 25th National and 3rd International Iranian Conference on Biomedical Engineering (ICBME)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Discovering Informative Regions in Iris Images to Predict Diabetes\",\"authors\":\"Parsa Moradi, Naghme Nazer, A. K. Ahmadi, H. Mohammadzade, Hasan Khojasteh Jafari\",\"doi\":\"10.1109/ICBME.2018.8703564\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Alternative medicine can be used to achieve the healing effects of the experimental medicine, it also can predict diseases and prevent them, but validity of them is unproven. Iridology is an alternative medicine that claims to predict tissue weaknesses in the body by looking at the iris. The main object of this paper is to validate the using of iridology to predict diabetes, to do so iris images of 106 diabetic patients and 124 healthy controls were obtained and evaluated. The designed method is completely automatic and independent of iridologists. Also a novel algorithm is developed to improve the efficiency by finding the best region of iris automatically. The results showed the accuracy of 91.8% in the best setting, which shows the effectiveness of the proposed method.\",\"PeriodicalId\":338286,\"journal\":{\"name\":\"2018 25th National and 3rd International Iranian Conference on Biomedical Engineering (ICBME)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 25th National and 3rd International Iranian Conference on Biomedical Engineering (ICBME)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICBME.2018.8703564\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 25th National and 3rd International Iranian Conference on Biomedical Engineering (ICBME)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBME.2018.8703564","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Discovering Informative Regions in Iris Images to Predict Diabetes
Alternative medicine can be used to achieve the healing effects of the experimental medicine, it also can predict diseases and prevent them, but validity of them is unproven. Iridology is an alternative medicine that claims to predict tissue weaknesses in the body by looking at the iris. The main object of this paper is to validate the using of iridology to predict diabetes, to do so iris images of 106 diabetic patients and 124 healthy controls were obtained and evaluated. The designed method is completely automatic and independent of iridologists. Also a novel algorithm is developed to improve the efficiency by finding the best region of iris automatically. The results showed the accuracy of 91.8% in the best setting, which shows the effectiveness of the proposed method.