| Deep learning for cardiac image segmentation: A review C Chen, C Qin, H Qiu, G Tarroni, J Duan, W Bai, D Rueckert Frontiers in Cardiovascular Medicine 7, 25, 2020 | 474 | 2020 |
| Self-supervision with superpixels: Training few-shot medical image segmentation without annotation C Ouyang, C Biffi, C Chen, T Kart, H Qiu, D Rueckert Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 117 | 2020 |
| Unsupervised multi-modal style transfer for cardiac MR segmentation C Chen, C Ouyang, G Tarroni, J Schlemper, H Qiu, W Bai, D Rueckert Statistical Atlases and Computational Models of the Heart. Multi-Sequence …, 2020 | 64 | 2020 |
| Realistic adversarial data augmentation for MR image segmentation C Chen, C Qin, H Qiu, C Ouyang, S Wang, L Chen, G Tarroni, W Bai, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 63 | 2020 |
| Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning A Hering, L Hansen, TCW Mok, ACS Chung, H Siebert, S Häger, A Lange, ... IEEE Transactions on Medical Imaging, 2022 | 49 | 2022 |
| Detecting Outliers with Foreign Patch Interpolation J Tan, B Hou, J Batten, H Qiu, B Kainz arXiv preprint arXiv:2011.04197, 2020 | 28 | 2020 |
| Learning Diffeomorphic and Modality-invariant Registration using B-splines H Qiu, C Qin, A Schuh, K Hammernik, D Rueckert Medical Imaging with Deep Learning, 2021 | 22 | 2021 |
| Self-supervised learning for few-shot medical image segmentation C Ouyang, C Biffi, C Chen, T Kart, H Qiu, D Rueckert IEEE Transactions on Medical Imaging 41 (7), 1837-1848, 2022 | 21 | 2022 |
| Biomechanics-informed neural networks for myocardial motion tracking in MRI C Qin, S Wang, C Chen, H Qiu, W Bai, D Rueckert Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 16 | 2020 |
| Enhancing MR image segmentation with realistic adversarial data augmentation C Chen, C Qin, C Ouyang, Z Li, S Wang, H Qiu, L Chen, G Tarroni, W Bai, ... Medical Image Analysis 82, 102597, 2022 | 13 | 2022 |
| Learning a Model-Driven Variational Network for Deformable Image Registration X Jia, A Thorley, W Chen, H Qiu, L Shen, IB Styles, HJ Chang, ... IEEE Transactions on Medical Imaging 41 (1), 199-212, 2021 | 13 | 2021 |
| Deep learning for cardiac motion estimation: supervised vs. unsupervised training H Qiu, C Qin, L Le Folgoc, B Hou, J Schlemper, D Rueckert Statistical Atlases and Computational Models of the Heart. Multi-Sequence …, 2020 | 12 | 2020 |
| MOOD 2020: A public Benchmark for Out-of-Distribution Detection and Localization on medical Images D Zimmerer, PM Full, F Isensee, P Jäger, T Adler, J Petersen, G Köhler, ... IEEE Transactions on Medical Imaging 41 (10), 2728-2738, 2022 | 9 | 2022 |
| Going deeper into cardiac motion analysis to model fine spatio-temporal features P Lu, H Qiu, C Qin, W Bai, D Rueckert, JA Noble Medical Image Understanding and Analysis: 24th Annual Conference, MIUA 2020 …, 2020 | 8 | 2020 |
| Is MC dropout Bayesian? L Le Folgoc, V Baltatzis, S Desai, A Devaraj, S Ellis, OEM Manzanera, ... arXiv preprint arXiv:2110.04286 2, 2021 | 6 | 2021 |
| Embedding Gradient-Based Optimization in Image Registration Networks H Qiu, K Hammernik, C Qin, C Chen, D Rueckert Medical Image Computing and Computer Assisted Intervention–MICCAI 2022: 25th …, 2022 | 3* | 2022 |
| Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte Carlo D Grzech, MF Azampour, H Qiu, B Glocker, B Kainz, LL Folgoc arXiv preprint arXiv:2110.13289, 2021 | | 2021 |
Daniel RueckertTechnical University of Munich and Imperial College LondonVerified email at tum.de
