| A feasibility of respiration prediction based on deep Bi-LSTM for real-time tumor tracking R Wang, X Liang, X Zhu, Y Xie IEEE Access 6, 51262-51268, 2018 | 78 | 2018 |
| xQSM: quantitative susceptibility mapping with octave convolutional and noise‐regularized neural networks Y Gao, X Zhu, BA Moffat, R Glarin, AH Wilman, GB Pike, S Crozier, F Liu, ... NMR in Biomedicine 34 (3), e4461, 2021 | 43 | 2021 |
| A deep unsupervised learning model for artifact correction of pelvis cone-beam CT G Dong, C Zhang, X Liang, L Deng, Y Zhu, X Zhu, X Zhou, L Song, X Zhao, ... Frontiers in Oncology 11, 686875, 2021 | 17 | 2021 |
| BFRnet: A deep learning-based MR background field removal method for QSM of the brain containing significant pathological susceptibility sources X Zhu, Y Gao, F Liu, S Crozier, H Sun Zeitschrift für Medizinische Physik, 2022 | 9 | 2022 |
| Deep grey matter quantitative susceptibility mapping from small spatial coverages using deep learning X Zhu, Y Gao, F Liu, S Crozier, H Sun Zeitschrift für Medizinische Physik 32 (2), 188-198, 2022 | 7 | 2022 |
| Key applications in deep learning based quantitative susceptibility mapping X Zhu The University of Queensland, 2024 | | 2024 |
Hongfu Sun / 孙洪福University of Newcastle; University of Queensland在 newcastle.edu.au 的电子邮件经过验证
