22 citations · 33 across the 10 of their papers we have counts for
10 papers
Generative Modeling in Sinogram Domain for Sparse-view CT Reconstruction
Bing Guan, Cailian Yang, Liu Zhang +5
The radiation dose in computed tomography (CT) examinations is harmful for patients but can be significantly reduced by intuitively decreasing the number of projection views. Reduc…
Generative Modeling in Structural-Hankel Domain for Color Image Inpainting
Zihao Li, Chunhua Wu, Shenglin Wu +3
In recent years, some researchers focused on using a single image to obtain a large number of samples through multi-scale features. This study intends to a brand-new idea that requ…
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…
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…
MRI Reconstruction Using Deep Energy-Based Model
Yu Guan, Zongjiang Tu, Shanshan Wang +3
Purpose: Although recent deep energy-based generative models (EBMs) have shown encouraging results in many image generation tasks, how to take advantage of the self-adversarial cog…
Variable Augmented Network for Invertible Modality Synthesis-Fusion
Yuhao Wang, Ruirui Liu, Zihao Li +2
As an effective way to integrate the information contained in multiple medical images under different modalities, medical image synthesis and fusion have emerged in various clinica…