| A sparse model-inspired deep thresholding network for exponential signal reconstruction—Application in fast biological spectroscopy Z Wang, D Guo, Z Tu, Y Huang, Y Zhou, J Wang, L Feng, D Lin, Y You, ... IEEE transactions on neural networks and learning systems 34 (10), 7578-7592, 2022 | 30 | 2022 |
| A fast self-learning subspace reconstruction method for non-uniformly sampled nuclear magnetic resonance spectroscopy Z Tu, H Liu, J Zhan, D Guo Applied Sciences 10 (11), 3939, 2020 | 7 | 2020 |
| Salt and pepper noise removal with multi-class dictionary learning and l0 norm regularizations D Guo, Z Tu, J Wang, M Xiao, X Du, X Qu Algorithms 12 (1), 7, 2018 | 7 | 2018 |
| CloudBrain-MRS: An intelligent cloud computing platform for in vivo magnetic resonance spectroscopy preprocessing, quantification, and analysis X Chen, J Li, D Chen, Y Zhou, Z Tu, M Lin, T Kang, J Lin, T Gong, L Zhu, ... Journal of Magnetic Resonance 358, 107601, 2024 | 6 | 2024 |
| Low-field NMR inversion based on low-rank and sparsity restraint of relaxation spectra SH Luo, LZ Xiao, Y Jin, JF Guo, XB Qu, ZR Tu, G Luo, C Liang Petroleum Science 19 (6), 2741-2756, 2022 | 6 | 2022 |
| Fast NMR spectroscopy reconstruction with a sliding window based Hankel matrix J Wu, R Xu, Y Huang, J Zhan, Z Tu, X Qu, D Guo Journal of Magnetic Resonance 342, 107283, 2022 | 6 | 2022 |
| 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 | 5 | 2023 |
| Hypercomplex low rank reconstruction for nmr spectroscopy Y Guo, J Zhan, Z Tu, Y Zhou, J Wu, Q Hong, Y Huang, V Orekhov, X Qu, ... Signal Processing 203, 108809, 2023 | 4 | 2023 |
| A partial sum of singular‐value‐based reconstruction method for non‐uniformly sampled NMR spectroscopy Z Tu, Z Wang, J Zhan, Y Huang, X Du, M Xiao, X Qu, D Guo IET Signal Processing 15 (1), 14-27, 2021 | 2 | 2021 |
| Low‐rank and sparse reconstruction for fast diffusion nuclear magnetic resonance spectroscopy D Guo, J Zhan, Y Zhou, Z Tu, Z Zhang, Z Chen, X Qu IET Signal Processing 15 (2), 88-97, 2021 | 1 | 2021 |
| Alternating Deep Low-Rank Approach for Exponential Function Reconstruction and Its Biomedical Magnetic Resonance Applications Y Huang, Z Wang, X Zhang, J Cao, Z Tu, M Lin, D Guo, X Qu arXiv preprint arXiv:2211.13479, 2022 | | 2022 |
| 基于低秩 Hankel 矩阵最小加权核范数的低强度谱峰重建 郭迪， 杜晓凤， 涂章仁， 肖旻， 屈小波 2018 第二十届全国波谱学学术年会会议论文摘要集, 2018 | | 2018 |
| Deep Learning Quantification of Magnetic Resonance Spectroscopy Based on Basis set and Exponential Priors D Chen, H Liu, Y Zhou, X Chen, Z Tu, L Lin, Z Wu, J Wang, D Guo, J Lin, ... | | |
| Research on Denoising of Magnetic Resonance Spectrum Based on Exponential Decomposition Constraint J Wu, T Qiu, Z Tu, D Guo, X Qu | | |
| 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 | | |
Xiaobo Qu (屈小波)Professor of Department of Electronic Science, Xiamen University在 xmu.edu.cn 的电子邮件经过验证
