5 citations · 10 across the 5 of their papers we have counts for
6 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…
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…
High-dimensional Assisted Generative Model for Color Image Restoration
Kai Hong, Chunhua Wu, Cailian Yang +4
This work presents an unsupervised deep learning scheme that exploiting high-dimensional assisted score-based generative model for color image restoration tasks. Considering that t…
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…
IFR-Net: Iterative Feature Refinement Network for Compressed Sensing MRI
Yiling Liu, Qiegen Liu, Minghui Zhang +3
To improve the compressive sensing MRI (CS-MRI) approaches in terms of fine structure loss under high acceleration factors, we have proposed an iterative feature refinement model (…
Denoising Auto-encoding Priors in Undecimated Wavelet Domain for MR Image Reconstruction
Siyuan Wang, Junjie Lv, Yuanyuan Hu +3
Compressive sensing is an impressive approach for fast MRI. It aims at reconstructing MR image using only a few under-sampled data in k-space, enhancing the efficiency of the data…