111 citations · 204 across the 9 of their papers we have counts for
4 papers · 1 filter
Unpaired MRI Super Resolution with Contrastive Learning
Hao Li, Quanwei Liu, Jianan Liu +4
Magnetic resonance imaging (MRI) is crucial for enhancing diagnostic accuracy in clinical settings. However, the inherent long scan time of MRI restricts its widespread applicabili…
Unsupervised Representation Learning for 3D MRI Super Resolution with Degradation Adaptation
Jianan Liu, Hao Li, Tao Huang +6
High-resolution (HR) magnetic resonance imaging is critical in aiding doctors in their diagnoses and image-guided treatments. However, acquiring HR images can be time-consuming and…
Performance of a GPU- and Time-Efficient Pseudo 3D Network for Magnetic Resonance Image Super-Resolution and Motion Artifact Reduction
Hao Li, Jianan Liu, Marianne Schell +8
Shortening acquisition time and reducing motion artifacts are the most critical challenges in magnetic resonance imaging (MRI). Deep learning-based image restoration has emerged as…
Edge, Structure and Texture Refinement for Retrospective High Quality MRI Restoration using Deep Learning
Hao Li, Jianan Liu
22. Shortening acquisition time and reducing the motion-artifact are two of the most critical issues in MRI. As a promising solution, high-quality MRI image restoration provides a…