  This chapter reviews recent developments of generative adversarial networks
(GAN)-based methods for medical and biomedical image synthesis tasks. These
methods are classified into conditional GAN and Cycle-GAN according to the
network architecture designs. For each category, a literature survey is given,
which covers discussions of the network architecture designs, highlights
important contributions and identifies specific challenges.
