Topic Collection
Generative AI in Ophthalmology
The field of ophthalmology has witnessed remarkable advancements in recent years, and the emergence of generative artificial intelligence (AI) techniques has further revolutionized research and clinical applications. This topic collection aims to explore the latest developments, challenges, and opportunities in the application of generative AI methods specifically tailored to ophthalmology.
Scope and topics:
British Journal of Ophthalmology invites researchers and practitioners from academia and industry to contribute their original research, reviews, or perspectives on various aspects of generative AI in ophthalmology. The topics of interest for this topic collection include, but are not limited to:
- Generative models for retinal image analysis and interpretation
- Synthetic data generation for ophthalmic imaging and diagnostics
- Deep learning approaches for ophthalmic image generation and augmentation
- Adversarial learning and generative adversarial networks (GANs) in ophthalmology
- Transfer learning and domain adaptation in generative AI for ophthalmology
- Explainability and interpretability of generative AI models in ophthalmic applications
- Clinical applications of generative AI in ophthalmology, such as disease diagnosis, prognosis, treatment planning and interactive question and answering
- Ethical considerations and challenges in the use of generative AI in ophthalmology
Guest Editors
Mingguang He
The Hong Kong Polytechnic University
Hong Kong, SAR of China
orcid.org/0000-0002-6912-2810

Pearse Keane
Moorfields Eye Hospital
London, UK
orcid.org/0000-0002-9239-745X

Aaron Lee
University of Washington
Seattle, USA
orcid.org/0000-0002-7452-1648
