37 citations · 41 across the 4 of their papers we have counts for
4 papers
Unsupervised Motion-Compensated Decomposition for Cardiac MRI Reconstruction via Neural Representation
Xuanyu Tian, Lixuan Chen, Qing Wu +4
Cardiac magnetic resonance (CMR) imaging is widely used to characterize cardiac morphology and function. To accelerate CMR imaging, various methods have been proposed to recover hi…
IMJENSE: Scan-specific Implicit Representation for Joint Coil Sensitivity and Image Estimation in Parallel MRI
Ruimin Feng, Qing Wu, Jie Feng +4
Parallel imaging is a commonly used technique to accelerate magnetic resonance imaging (MRI) data acquisition. Mathematically, parallel MRI reconstruction can be formulated as an i…
Spatiotemporal implicit neural representation for unsupervised dynamic MRI reconstruction
Jie Feng, Ruimin Feng, Qing Wu +3
Supervised Deep-Learning (DL)-based reconstruction algorithms have shown state-of-the-art results for highly-undersampled dynamic Magnetic Resonance Imaging (MRI) reconstruction. H…
MoDL-QSM: Model-based Deep Learning for Quantitative Susceptibility Mapping
Ruimin Feng, Jiayi Zhao, He Wang +8
Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases. However, the intrinsic ill-posed inverse…