基于CNN的糖尿病视网膜病变严重程度分析模型,以阿育吠陀医学视角辅助医学治疗

Chris S Peter, Manu Elappila, A. Swathi
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引用次数: 1

摘要

糖尿病是现代主要的生活方式疾病之一。糖尿病视网膜病变是导致失明的主要原因,甚至在很小的时候。眼部疾病的临床评估是通过视觉检查和探查来完成的。视网膜血管分割是一项重要的技术,它有助于检测血管中发生的变化,并提供血管位置的信息。本文的工作旨在检测和分析糖尿病视网膜病变引起的视网膜血管变化。利用数字成像技术,严重程度筛查技术有助于糖尿病视网膜病变的诊断。该模型以这样一种方式工作,它有助于阿育吠陀治疗糖尿病视网膜病变的方法。根据疾病的严重程度和不同的分类对数据元素进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CNN based Model for Severity Analysis of Diabetic Retinopathy to aid Medical Treatment with Ayurvedic Perspective
One among the major modern life-style diseases is Diabetes. Diabetic Retinopathy is a major cause for blindness even at an early age. Clinical assessments for eye disease are done using visual examinations and probing. Retinal vessel segmentation is an important technique which helps in detection of changes that happens in blood vessel as well as gives information regarding the location of vessels. The work presented in this paper tries to detect and analyze the changes occurred in the blood vessels of human retina caused by diabetic retinopathy. Using digital imaging techniques, the severity screening technique facilitates the diagnosis of diabetic retinopathy. The model works in such a way that it helps the Ayurvedic treatment methodology for Diabetic Retinopathy. Results are obtained to categorize the data elements according to the severity of the disease and different classifications.
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