The development of deep learning (DL) systems requires a large amount of data, which may be limited by costs, protection of patient information and low prevalence of some conditions. Recent developments in artificial intelligence techniques have provided an innovative alternative to this challenge via the synthesis of biomedical images within a DL framework known as generative adversarial networks (GANs). This paper aims to introduce how GANs can be deployed for image synthesis in ophthalmology and to discuss the potential applications of GANs-produced images.

中文翻译：

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眼科生成对抗网络：它们是什么以及如何使用它们？

深度学习（DL）系统的开发需要大量数据，这可能会受到成本、患者信息保护和某些疾病患病率较低的限制。人工智能技术的最新发展为这一挑战提供了一种创新的替代方案，即在称为生成对抗网络 (GAN) 的深度学习框架内合成生物医学图像。本文旨在介绍如何将 GAN 用于眼科图像合成，并讨论 GAN 生成的图像的潜在应用。