MRI Reconstruction Using Deep Energy-Based Model

1 code implementation • 7 Sep 2021 • Yu Guan, Zongjiang Tu, Shanshan Wang, Qiegen Liu, Yuhao Wang, Dong Liang

In contrast to other generative models for reconstruction, the proposed method utilizes deep energy-based information as the image prior in reconstruction to improve the quality of image.

Image Generation MRI Reconstruction

K-space and Image Domain Collaborative Energy based Model for Parallel MRI Reconstruction

1 code implementation • 21 Mar 2022 • Zongjiang Tu, Chen Jiang, Yu Guan, Shanshan Wang, Jijun Liu, Qiegen Liu, Dong Liang

Decreasing magnetic resonance (MR) image acquisition times can potentially make MR examinations more accessible.

MRI Reconstruction

WKGM: Weight-K-space Generative Model for Parallel Imaging Reconstruction

1 code implementation • 8 May 2022 • Zongjiang Tu, Die Liu, Xiaoqing Wang, Chen Jiang, Pengwen Zhu, Minghui Zhang, Shanshan Wang, Dong Liang, Qiegen Liu

Deep learning based parallel imaging (PI) has made great progresses in recent years to accelerate magnetic resonance imaging (MRI).