Synopsis

In this talk, we will briefly review the current trends of deep learning and explain how they have been employed in MR imaging. In particular, we review the principles of Transformer, generative adversarial nets, optimal transport, cycleGAN, noise2void, noise2score, and score-based diffusion model. MR application of these methods will be also reviewed.