104 citations · 217 across the 12 of their papers we have counts for
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eess.IV2023★ 8 cited
Unsupervised Polychromatic Neural Representation for CT Metal Artifact Reduction
Qing Wu, Lixuan Chen, Ce Wang +4
Emerging neural reconstruction techniques based on tomography (e.g., NeRF, NeAT, and NeRP) have started showing unique capabilities in medical imaging. In this work, we present a n…
eess.IV2023
Self-supervised arbitrary scale super-resolution framework for anisotropic MRI
Haonan Zhang, Yuhan Zhang, Qing Wu +7
In this paper, we propose an efficient self-supervised arbitrary-scale super-resolution (SR) framework to reconstruct isotropic magnetic resonance (MR) images from anisotropic MRI…
eess.IV2023★ 37 cited
Spatiotemporal implicit neural representation for unsupervised dynamic MRI reconstruction
Jie Feng, Ruimin Feng, Qing Wu +3
Supervised Deep-Learning (DL)-based reconstruction algorithms have shown state-of-the-art results for highly-undersampled dynamic Magnetic Resonance Imaging (MRI) reconstruction. H…