Human Retina

The human retina is a crucial focus of biomedical research, with primary objectives centered on improving the early detection and diagnosis of various eye diseases and systemic conditions reflected in retinal vasculature. Current research heavily utilizes deep learning, employing convolutional neural networks (like U-Net, ResNet, Inception, and VGG) and graph-based classifiers to analyze retinal images (fundus photography, OCT, OCTA) for automated segmentation of structures like photoreceptors and blood vessels, and for disease classification (e.g., diabetic retinopathy, Alzheimer's disease). These advancements offer significant potential for improving diagnostic accuracy, streamlining clinical workflows, and enabling earlier interventions, ultimately impacting patient care and advancing our understanding of eye-brain connections.