5 citations · 15 across the 12 of their papers we have counts for
4 papers · 1 filter
Low-rank Tensor Assisted K-space Generative Model for Parallel Imaging Reconstruction
Wei Zhang, Zengwei Xiao, Hui Tao +3
Although recent deep learning methods, especially generative models, have shown good performance in fast magnetic resonance imaging, there is still much room for improvement in hig…
Universal Generative Modeling for Calibration-free Parallel Mr Imaging
Wanqing Zhu, Bing Guan, Shanshan Wang +2
The integration of compressed sensing and parallel imaging (CS-PI) provides a robust mechanism for accelerating MRI acquisitions. However, most such strategies require the explicit…
Virtual Coil Augmentation Technology for MR Coil Extrapolation via Deep Learning
Cailian Yang, Xianghao Liao, Yuhao Wang +2
Magnetic resonance imaging (MRI) is a widely used medical imaging modality. However, due to the limitations in hardware, scan time, and throughput, it is often clinically challengi…
Joint Intensity-Gradient Guided Generative Modeling for Colorization
Kai Hong, Jin Li, Wanyun Li +4
This paper proposes an iterative generative model for solving the automatic colorization problem. Although previous researches have shown the capability to generate plausible color…