Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.
Michigan Medicine, University of Michigan, Ann Arbor, USA.
Surv Ophthalmol. 2025 Jan-Feb;70(1):1-11. doi: 10.1016/j.survophthal.2024.04.009. Epub 2024 May 16.
Generative artificial intelligence (AI) has revolutionized medicine over the past several years. A generative adversarial network (GAN) is a deep learning framework that has become a powerful technique in medicine, particularly in ophthalmology for image analysis. In this paper we review the current ophthalmic literature involving GANs, and highlight key contributions in the field. We briefly touch on ChatGPT, another application of generative AI, and its potential in ophthalmology. We also explore the potential uses for GANs in ocular imaging, with a specific emphasis on 3 primary domains: image enhancement, disease identification, and generating of synthetic data. PubMed, Ovid MEDLINE, Google Scholar were searched from inception to October 30, 2022, to identify applications of GAN in ophthalmology. A total of 40 papers were included in this review. We cover various applications of GANs in ophthalmic-related imaging including optical coherence tomography, orbital magnetic resonance imaging, fundus photography, and ultrasound; however, we also highlight several challenges that resulted in the generation of inaccurate and atypical results during certain iterations. Finally, we examine future directions and considerations for generative AI in ophthalmology.
生成式人工智能（AI）在过去几年中彻底改变了医学领域。生成式对抗网络（GAN）是一种深度学习框架，已成为医学领域（尤其是眼科领域的图像分析）的强大技术。本文我们回顾了当前涉及 GAN 的眼科文献，并重点介绍了该领域的关键贡献。我们简要探讨了生成式 AI 的另一种应用——ChatGPT，及其在眼科领域的潜在应用。我们还探讨了 GAN 在眼部成像中的潜在用途，特别关注 3 个主要领域：图像增强、疾病识别和合成数据生成。我们从 2022 年 10 月 30 日开始在 PubMed、Ovid MEDLINE 和 Google Scholar 上搜索 GAN 在眼科中的应用，以确定其在眼科中的应用。本综述共纳入 40 篇论文。我们涵盖了 GAN 在眼科相关成像中的各种应用，包括光学相干断层扫描、眼眶磁共振成像、眼底摄影和超声；然而，我们还强调了在某些迭代过程中导致生成不准确和非典型结果的几个挑战。最后，我们探讨了生成式 AI 在眼科领域的未来方向和考虑因素。
