54 citations · 248 across the 37 of their papers we have counts for
5 papers · 1 filter
Universal Generative Modeling in Dual-domain for Dynamic MR Imaging
Chuanming Yu, Yu Guan, Ziwen Ke +2
Dynamic magnetic resonance image reconstruction from incomplete k-space data has generated great research interest due to its capability to reduce scan time. Never-theless, the rec…
WKGM: Weight-K-space Generative Model for Parallel Imaging Reconstruction
Zongjiang Tu, Die Liu, Xiaoqing Wang +6
Deep learning based parallel imaging (PI) has made great progresses in recent years to accelerate magnetic resonance imaging (MRI). Nevertheless, it still has some limitations, suc…
Dual-domain Attention-based Deep Network for Sparse-view CT Artifact Reduction
Xiang Gao, Ting Su, Jiongtao Zhu +7
Due to the wide applications of X-ray computed tomography (CT) in medical imaging activities, radiation exposure has become a major concern for public health. Sparse-view CT is a p…
K-space and Image Domain Collaborative Energy based Model for Parallel MRI Reconstruction
Zongjiang Tu, Chen Jiang, Yu Guan +4
Decreasing magnetic resonance (MR) image acquisition times can potentially make MR examinations more accessible. Prior arts including the deep learning models have been devoted to…
Variable Augmented Network for Invertible MR Coil Compression
Xianghao Liao, Shanshan Wang, Lanlan Tu +3
A large number of coils are able to provide enhanced signal-to-noise ratio and improve imaging performance in parallel imaging. Nevertheless, the increasing growth of coil number s…