The Role of Artificial Intelligence in Ophthalmic Imaging: Current Applications, Challenges, and Future Directions

Abstract

Artificial intelligence (AI) has emerged as a transformative technology in ophthalmology, particularly in the analysis and interpretation of ophthalmic imaging. The image-rich nature of ophthalmological practice, combined with advances in deep learning and computer vision, has created unprecedented opportunities for automated disease detection, diagnosis, and monitoring. This comprehensive review examines the current state of AI applications in ophthalmological imaging, including fundus photography, optical coherence tomography (OCT), and optical coherence tomography angiography (OCTA). We discuss the clinical impact of AI-driven screening programs, the challenges of implementation in real-world settings, and future directions including generative AI and multimodal approaches. The integration of AI in ophthalmological imaging represents a paradigm shift toward more accessible, efficient, and precise eye care delivery.