| Accelerated nuclear magnetic resonance spectroscopy with deep learning X Qu, Y Huang, H Lu, T Qiu, D Guo, T Agback, V Orekhov, Z Chen Angewandte Chemie 132 (26), 10383-10386, 2020 | 156 | 2020 |
| Low rank enhanced matrix recovery of hybrid time and frequency data in fast magnetic resonance spectroscopy H Lu, X Zhang, T Qiu, J Yang, J Ying, D Guo, Z Chen, X Qu IEEE Transactions on Biomedical Engineering 65 (4), 809-820, 2017 | 37 | 2017 |
| Review and prospect: NMR spectroscopy denoising and reconstruction with low‐rank Hankel matrices and tensors T Qiu, Z Wang, H Liu, D Guo, X Qu Magnetic Resonance in Chemistry 59 (3), 324-345, 2021 | 36 | 2021 |
| An automatic denoising method for NMR spectroscopy based on low-rank Hankel model T Qiu, W Liao, Y Huang, J Wu, D Guo, D Liu, X Wang, JF Cai, B Hu, X Qu IEEE Transactions on Instrumentation and Measurement 70, 1-12, 2021 | 17 | 2021 |
| Magnetic resonance spectroscopy deep learning denoising using few in vivo data D Chen, W Hu, H Liu, Y Zhou, T Qiu, Y Huang, Z Wang, M Lin, L Lin, Z Wu, ... IEEE Transactions on Computational Imaging, 2023 | 9 | 2023 |
| High-fidelity spectroscopy reconstruction in accelerated NMR X Qu, T Qiu, D Guo, H Lu, J Ying, M Shen, B Hu, V Orekhov, Z Chen Chemical communications 54 (78), 10958-10961, 2018 | 9 | 2018 |
| XCloud-VIP: Virtual peak enables highly accelerated NMR spectroscopy and faithful quantitative measures D Guo, Z Tu, Y Guo, Y Zhou, J Wang, Z Wang, T Qiu, M Xiao, Y Chen, ... IEEE Transactions on Computational Imaging 9, 1043-1057, 2023 | 4 | 2023 |
| Coil Combination of Multichannel Single Voxel Magnetic Resonance Spectroscopy with Repeatedly Sampled In Vivo Data W Hu, H Liu, D Chen, T Qiu, H Sun, C Xiong, J Lin, D Guo, H Chen, X Qu Molecules 26 (13), 3896, 2021 | 3 | 2021 |
| Denoising single voxel magnetic resonance spectroscopy with deep learning on repeatedly sampled in vivo data W Hu, D Chen, T Qiu, H Chen, X Chen, L Yang, G Yan, D Guo, X Qu arXiv e-prints, arXiv: 2101.11442, 2021 | 3 | 2021 |
| A low rank Hankel matrix reconstruction method for ultrafast magnetic resonance spectroscopy H Lu, X Zhang, T Qiu, J Yang, D Guo, Z Chen, X Qu 2017 39th Annual International Conference of the IEEE Engineering in …, 2017 | 3 | 2017 |
| Resolution enhancement of NMR by decoupling with the low-rank Hankel model T Qiu, A Jahangiri, X Han, D Lesovoy, T Agback, P Agback, A Achour, ... Chemical Communications 59 (36), 5475-5478, 2023 | 1 | 2023 |
| CloudBrain-NMR: An Intelligent Cloud Computing Platform for NMR Spectroscopy Processing, Reconstruction and Analysis D Guo, S Li, J Liu, Z Tu, T Qiu, J Xu, L Feng, D Lin, Q Hong, M Lin, Y Lin, ... arXiv preprint arXiv:2309.07178, 2023 | | 2023 |
| An auto-parameter denoising method for nuclear magnetic resonance spectroscopy based on low-rank Hankel matrix T Qiu, W Liao, D Guo, D Liu, X Wang, JF Cai, X Qu arXiv preprint arXiv:2001.11815, 2020 | | 2020 |
| Gaussian noise removal with exponential functions and spectral norm of weighted Hankel matrices T Qiu, W Liao, D Guo, D Liu, X Wang, X Qu CoRR, 2020 | | 2020 |
| Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning (中文, English) X Qu, Y Huang, H Lu, T Qiu, D Guo, V Orekhov, Z Chen | | |
| Deep Learning-based Fast Magnetic Resonance Spectroscopy X Qu, Y Huang, H Lu, T Qiu, D Guo, T Agback, V Orekhov, Z Chen | | |
| Magnetic Resonance Spectroscopy Denoising with the Automatic Regularization Parameter Estimation in Low-Rank Hankel Matrix Reconstruction T Qiu, W Liao, D Guo, Z Tu, B Hu, X Qu | | |
| A Subspace-based Reliable NMR Spectroscopy Reconstruction D Guo, Z Tu, T Qiu, X Du, M Xiao, V Orekhov, X Qu | | |
| Low Rank Enhanced Matrix Recovery of Hybrid Time and Frequency Data in Fast Magnetic Resonance Spectroscopy (中文, English) H Lu, X Zhang, T Qiu, J Yang, J Ying, D Guo, Z Chen, X Qu | | |
| Joint Sparsity and Low Rankness-based Spectroscopy Reconstruction for Magnetic Resonance Diffusion-Ordered NMR D Guo, Z Tu, Z Zhang, T Qiu, X Du, M Xiao, Z Chen, X Qu | | |
