Retinal Disease

Retinal disease research focuses on developing accurate and efficient diagnostic tools, primarily leveraging advanced imaging techniques like optical coherence tomography (OCT) and fundus photography. Current research emphasizes the use of deep learning models, including convolutional neural networks (CNNs), transformers, and generative adversarial networks (GANs), often incorporating 3D data analysis and multi-modal learning to improve diagnostic accuracy and robustness across diverse datasets and imaging modalities. These advancements hold significant potential for improving early detection and management of various retinal diseases, ultimately impacting patient care and reducing the global burden of vision impairment.