| CT-based automatic spine segmentation using patch-based deep learning SF Qadri, H Lin, L Shen, M Ahmad, S Qadri, S Khan, M Khan, SS Zareen, ... International Journal of Intelligent Systems 2023, 1-14, 2023 | 46 | 2023 |
| Novel automatic first-arrival picking method for ultrasound sound-speed tomography X Qu, T Azuma, H Imoto, R Raufy, H Lin, H Nakamura, S Tamano, ... Japanese Journal of Applied Physics 54 (7S1), 07HF10, 2015 | 37 | 2015 |
| ABCD neurocognitive prediction challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression A Mihalik, M Brudfors, M Robu, FS Ferreira, H Lin, A Rau, T Wu, ... Challenge in Adolescent Brain Cognitive Development Neurocognitive …, 2019 | 30 | 2019 |
| Deep learning for low-field to high-field MR: image quality transfer with probabilistic decimation simulator H Lin, M Figini, R Tanno, SB Blumberg, E Kaden, G Ogbole, BJ Brown, ... Machine Learning for Medical Image Reconstruction: Second International …, 2019 | 20 | 2019 |
| Phase aberration correction by multi-stencils fast marching method using sound speed image in ultrasound computed tomography X Qu, T Azuma, H Lin, H Imoto, S Tamano, S Takagi, S Umemura, ... Medical Imaging 2016: Ultrasonic Imaging and Tomography 9790, 341-347, 2016 | 19 | 2016 |
| Computational cost reduction by avoiding ray-linking iteration in bent-ray method for sound speed image reconstruction in ultrasound computed tomography X Qu, T Azuma, H Lin, H Nakamura, S Tamano, S Takagi, S Umemura, ... Japanese Journal of Applied Physics 56 (7S1), 07JF14, 2017 | 14 | 2017 |
| Robust contrast source inversion method with automatic choice rule of regularization parameters for ultrasound waveform tomography H Lin, T Azuma, X Qu, S Takagi Japanese Journal of Applied Physics 55 (7S1), 07KB08, 2016 | 13 | 2016 |
| ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology NP Oxtoby, FS Ferreira, A Mihalik, T Wu, M Brudfors, H Lin, A Rau, ... Challenge in Adolescent Brain Cognitive Development Neurocognitive …, 2019 | 11 | 2019 |
| Learning to address intra-segment misclassification in retinal imaging Y Zhou, M Xu, Y Hu, H Lin, J Jacob, PA Keane, DC Alexander Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 8 | 2021 |
| Image quality transfer enhances contrast and resolution of low-field brain mri in african paediatric epilepsy patients M Figini, H Lin, G Ogbole, FD Arco, SB Blumberg, DW Carmichael, ... arXiv preprint arXiv:2003.07216, 2020 | 8 | 2020 |
| Limb muscle sound speed estimation by ultrasound computed tomography excluding receivers in bone shadow X Qu, T Azuma, H Lin, H Takeuchi, K Itani, S Tamano, S Takagi, I Sakuma Medical Imaging 2017: Ultrasonic Imaging and Tomography 10139, 313-320, 2017 | 8 | 2017 |
| Feasibility of data-driven, model-free quantitative MRI protocol design: Application to brain and prostate diffusion-relaxation imaging F Grussu, SB Blumberg, M Battiston, LS Kakkar, H Lin, A Ianuş, ... Frontiers in Physics 9, 752208, 2021 | 6 | 2021 |
| Low-field magnetic resonance image enhancement via stochastic image quality transfer H Lin, M Figini, F D’Arco, G Ogbole, R Tanno, SB Blumberg, L Ronan, ... Medical Image Analysis 87, 102807, 2023 | 5 | 2023 |
| Progressive subsampling for oversampled data-application to quantitative MRI SB Blumberg, H Lin, F Grussu, Y Zhou, M Figini, DC Alexander International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 5 | 2022 |
| “Select and retrieve via direct upsampling” network (SARDU-Net): a data-driven, model-free, deep learning approach for quantitative MRI protocol design F Grussu, SB Blumberg, M Battiston, LS Kakkar, H Lin, A Ianuş, ... bioRxiv, 2020.05. 26.116491, 2020 | 5 | 2020 |
| Adaptively re-weighting multi-loss untrained transformer for sparse-view cone-beam CT reconstruction M Wu, Y Xu, Y Xu, G Wu, Q Chen, H Lin arXiv preprint arXiv:2203.12476, 2022 | 4 | 2022 |
| Generalised super resolution for quantitative MRI using self-supervised mixture of experts H Lin, Y Zhou, PJ Slator, DC Alexander Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 4 | 2021 |
| Deep-learning-based ultrasound sound-speed tomography reconstruction with Tikhonov pseudo-inverse priori X Qu, C Ren, G Yan, D Zheng, W Tang, S Wang, H Lin, J Zhang, J Jiang Ultrasound in medicine & biology 48 (10), 2079-2094, 2022 | 3 | 2022 |
| Complex transformer network for single-angle plane-wave imaging X Qu, C Ren, Z Wang, S Fan, D Zheng, S Wang, H Lin, J Jiang, W Xing Ultrasound in Medicine & Biology 49 (10), 2234-2246, 2023 | 2 | 2023 |
| Evaluation of adjoint methods in photoacoustic tomography with under-sampled sensors H Lin, T Azuma, MB Unlu, S Takagi Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 1 | 2018 |
Xiaolei QuBeihang UniversityVerified email at buaa.edu.cn
