Ophthalmic Image

Ophthalmic image analysis focuses on developing automated methods for extracting clinically relevant information from various eye imaging modalities, such as optical coherence tomography (OCT) and scanning laser ophthalmoscopy (SLO), to improve diagnostic accuracy and efficiency. Current research emphasizes the development of robust and efficient deep learning models, including generative adversarial networks (GANs) for data augmentation and various transformer-based architectures for image analysis and report generation, often incorporating multimodal data and clinical knowledge graphs. These advancements aim to address challenges like artifact tolerance, improve model interpretability, and ultimately facilitate earlier and more accurate diagnosis of eye diseases, leading to better patient outcomes.