Diabetic Retinopathy Detection Using Deep Learning

K. Swathi, E. S. N. Joshua, B. Reddy, N. Rao
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Abstract

Diabetes is one of the hazardous diseases in present era. Diabetic retinopathy is an eye disease which is caused due to diabetes. This condition affects the retina (blood vessels at the back of the eye), resulting in blindness. Diabetic retinopathy can occur in numerous ways, from no symptoms to minor vision impairments. In order to check whether a person got affected or not, the patient should visit a hospital, for the reports and should wait for enormous time. With the development of deep learning techniques, we have the ability to look into the problem. The aim of the examination is to develop a system which might classify the diabetic retinopathy disease of a patient with a better accuracy. The model we develop will remove the noise from fundus images uploaded by user by using filtering techniques and give accurate result. This project is a deep learning model integrated with web application in order to interact with users. There by the Diabetic Retinopathy detection model enhances medical care.
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基于深度学习的糖尿病视网膜病变检测
糖尿病是当今时代的危害疾病之一。糖尿病视网膜病变是由糖尿病引起的一种眼部疾病。这种情况会影响视网膜(眼睛后面的血管),导致失明。糖尿病视网膜病变可以以多种方式发生,从无症状到轻微的视力损害。为了检查一个人是否受到感染,病人应该去医院,为了报告,应该等待很长时间。随着深度学习技术的发展,我们有能力研究问题。检查的目的是开发一种系统,可以更准确地对患者的糖尿病视网膜病变进行分类。该模型将利用滤波技术去除用户上传的眼底图像中的噪声,并给出准确的结果。这个项目是一个与web应用程序集成的深度学习模型,以便与用户交互。从而通过糖尿病视网膜病变的检测模型提高医疗护理水平。
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