Deep Learning Based Approach for the Detection of Diabetic Retinopathy and Glaucoma
摘要
The diagnosis of diabetic retinopathy has historically depended on specialists analyzing digital retinal images, but these knowledgeable individuals are in short supply. Interest in using computer assistance for monitoring has increased because of this challenge. The goal of our project is to present a novel approach to retinal image analysis. We are concentrating on identifying problems with blood vessels and exudates, which are important markers for comprehending retinal diseases such as diabetes in their early stages and Glaucoma. Our goal in researching these alterations in the blood vessels of the eye is to create a computerized system that will aid in the diagnosis of eye disorders. The goal of this project is to provide a more straightforward and effective method for assessing retinal health. One important objective is to use technology to identify problems more quickly and precisely, particularly when there aren’t as many expert observers as possible available. The goal of this research is to develop a trustworthy instrument that will facilitate the early identification and evaluation of retinal disorders, ultimately leading to better outcomes for eye health.