Retinal Image

Retinal image analysis focuses on extracting clinically relevant information from images of the retina to aid in the diagnosis and management of various eye diseases and systemic conditions. Current research emphasizes developing and refining automated methods for image analysis, leveraging deep learning architectures like convolutional neural networks (CNNs), transformers, and generative adversarial networks (GANs) for tasks such as image registration, segmentation (e.g., blood vessel segmentation, layer segmentation), classification (e.g., diabetic retinopathy grading), and even image synthesis. These advancements hold significant potential for improving diagnostic accuracy, efficiency, and accessibility in ophthalmology, particularly in addressing the growing global burden of retinal diseases.