Unpaired deep learning for accelerated MRI using optimal transport driven cycleGAN

A novel unpaired learning scheme for accelerated MRI, OT-cycleGAN was extensively applied and was found effective for the reconstruction of multi-coil static MRI.

Unpaired training of deep learning tMRA for flexible spatio-temporal resolution

OT-cycleGAN for the reconstruction of time resolved magnetic resonance angiography (MRA) was proposed. The derived method enables flexible control of sptial and temporal resolution.

Simultaneous super-resolution and motion artifact removal in diffusion-weighted MRI using unsupervised deep learning

Unsupervised deep learning for simultaneous super-resolution and motion artifact removal of diffusion-weighted MRI scans is proposed.

Two-Stage Deep Learning for Accelerated 3D Time-of-Flight MRA without Matched Training Data

Two-stage unsupervised reconstruction method for 3D TOF-MRA is developed. A novel projection discriminator in the axial reconstruction step drastically enhances the vessel visiblity.

Deep Learning Fast MRI Using Channel Attention in Magnitude Domain

BarbellNet, which consists of long stack of residual channel attention block(RCAB) was proposed for the reconstruction of fast MRI reconstruction. Reconstruction results through this model was placed 6th in the NeurIPS2020 fastMRI challenge.