Deep Learning-Based Macular Edema Evaluation and Unravelling the Prognostic Landscape for Vision Impairment Risk

Amidst the current surge in health challenges, macular edema stands out as a significant issue, often complicating various retinal diseases.This condition, characterized by the swelling of the macula, a part of the retina crucial for sharp, central vision, can be a complication of various eye diseases.Conditions such as diabetic retinopathy, age-related macular degeneration, and vascular diseases may lead to macular edema.This condition not only poses a threat to vision but can, in severe cases, lead to blindness.Addressing the complexities of diagnosis and predicting the potential progression to blindness associated with macular edema has become a top priority in clinical research.The integration of advanced imaging technologies and Deep Learning in the assessment of macular edema offers a promising approach to enhance diagnostic precision and predict the risk of blindness.So, in this project a Deep Learning model is to be made which classifies retinal images of a person into various levels of chance of occurrence of blindness.The Deep Learning model uses the algorithms like U-Net, MobileNetV3.