6 citations · 6 across the 5 of their papers we have counts for
5 papers
PhyMRI-SR: Toward Physics-Aware MRI Image Super-Resolution
Lihua Wei, Huatong Gao, Jia Gong +4
Magnetic resonance imaging (MRI) super-resolution is vital for improving diagnostic accessibility, yet most methods treat it as a deterministic mapping from a fixed low-resolution…
Unsupervised Radar Point Cloud Enhancement via Arbitrary LiDAR Guided Diffusion Prior
Yanlong Yang, Jianan Liu, Guanxiong Luo +4
In industrial automation, radar is a critical sensor in machine perception. However, the angular resolution of radar is inherently limited by the Rayleigh criterion, which depends…
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…
Efficient MRI Parallel Imaging Reconstruction by K-Space Rendering via Generalized Implicit Neural Representation
Hao Li, Yusheng Zhou, Jianan Liu +5
High-resolution magnetic resonance imaging (MRI) is essential in clinical diagnosis. However, its long acquisition time remains a critical issue. Parallel imaging (PI) is a common…
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…