Generative adversarial network in medical imaging: A review

•The number of publications in medical imaging using adversarial training scheme are increasing rapidly.•By surveying 150 published articles (including preprints), we have observed the effectiveness of adversarial training in all canonical tasks in medical image analysis.•Generative adversarial networks are most popular in medical image synthesis and are used for data augmentation to alleviate the data scarcity and overfitting problem.•Well trained discriminator can be regarded as a learned prior for the normal images so that it can be used as a regularizer.•Other potential applications of GANs such as image captioning, cross modality translation, automatic Magnetic resonance protocol generation have also been discussed.