M. Chazi-Solis, C. Cajamarca-Bueno, E. Pinos-Vélez, V. Robles-Bykbaev, C. Chacón
{"title":"基于视网膜神经纤维厚度分析的计算机视觉方法评估青光眼风险","authors":"M. Chazi-Solis, C. Cajamarca-Bueno, E. Pinos-Vélez, V. Robles-Bykbaev, C. Chacón","doi":"10.1109/CONIITI.2018.8587082","DOIUrl":null,"url":null,"abstract":"According to estimations of the World Health Organization (WHO), approximately 4.5 million persons will become blind due to the primary Glaucoma. For these reasons, in this paper, we present a simple approach to estimate the risk of suffering from glaucoma that presents a patient. Our proposal relies on the automatic analysis of Optical Coherence Tomography (OCT) images through the calculus of nerve fiber and ganglionary vessels areas. To this aim, our system separates the two areas mentioned before through computer vision techniques and the Newton Interpolation Method. Once the two areas are separated, the system determines the size of each of them. This proposal was validated through an experiment carried out with OCT 30 images (per eye). The results are encouraging, and the suggestions provided by the system match with medical diagnosis.","PeriodicalId":292178,"journal":{"name":"2018 Congreso Internacional de Innovación y Tendencias en Ingeniería (CONIITI)","volume":"323 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Computer Vision Approach Based on the Retinal Nerve Fiber Thickness Analysis to Estimate the Risk of Suffering Glaucoma\",\"authors\":\"M. Chazi-Solis, C. Cajamarca-Bueno, E. Pinos-Vélez, V. Robles-Bykbaev, C. Chacón\",\"doi\":\"10.1109/CONIITI.2018.8587082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"According to estimations of the World Health Organization (WHO), approximately 4.5 million persons will become blind due to the primary Glaucoma. For these reasons, in this paper, we present a simple approach to estimate the risk of suffering from glaucoma that presents a patient. Our proposal relies on the automatic analysis of Optical Coherence Tomography (OCT) images through the calculus of nerve fiber and ganglionary vessels areas. To this aim, our system separates the two areas mentioned before through computer vision techniques and the Newton Interpolation Method. Once the two areas are separated, the system determines the size of each of them. This proposal was validated through an experiment carried out with OCT 30 images (per eye). The results are encouraging, and the suggestions provided by the system match with medical diagnosis.\",\"PeriodicalId\":292178,\"journal\":{\"name\":\"2018 Congreso Internacional de Innovación y Tendencias en Ingeniería (CONIITI)\",\"volume\":\"323 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Congreso Internacional de Innovación y Tendencias en Ingeniería (CONIITI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CONIITI.2018.8587082\",\"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 Congreso Internacional de Innovación y Tendencias en Ingeniería (CONIITI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONIITI.2018.8587082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Computer Vision Approach Based on the Retinal Nerve Fiber Thickness Analysis to Estimate the Risk of Suffering Glaucoma
According to estimations of the World Health Organization (WHO), approximately 4.5 million persons will become blind due to the primary Glaucoma. For these reasons, in this paper, we present a simple approach to estimate the risk of suffering from glaucoma that presents a patient. Our proposal relies on the automatic analysis of Optical Coherence Tomography (OCT) images through the calculus of nerve fiber and ganglionary vessels areas. To this aim, our system separates the two areas mentioned before through computer vision techniques and the Newton Interpolation Method. Once the two areas are separated, the system determines the size of each of them. This proposal was validated through an experiment carried out with OCT 30 images (per eye). The results are encouraging, and the suggestions provided by the system match with medical diagnosis.