  Generative adversarial networks (GANs) and other adversarial methods are
based on a game-theoretical perspective on joint optimization of two neural
networks as players in a game. Adversarial techniques have been extensively
used to synthesize and analyze biomedical images. We provide an introduction to
GANs and adversarial methods, with an overview of biomedical image analysis
tasks that have benefited from such methods. We conclude with a discussion of
strengths and limitations of adversarial methods in biomedical image analysis,
and propose potential future research directions.
