| MRI k-space motion artefact augmentation: model robustness and task-specific uncertainty R Shaw, C Sudre, S Ourselin, MJ Cardoso | 54 | 2018 |
| A k-space model of movement artefacts: application to segmentation augmentation and artefact removal R Shaw, CH Sudre, T Varsavsky, S Ourselin, MJ Cardoso IEEE transactions on medical imaging 39 (9), 2881-2892, 2020 | 37 | 2020 |
| NTIRE 2022 challenge on high dynamic range imaging: Methods and results E Pérez-Pellitero, S Catley-Chandar, R Shaw, A Leonardis, R Timofte, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 33 | 2022 |
| Neuromorphologicaly-preserving volumetric data encoding using VQ-VAE PD Tudosiu, T Varsavsky, R Shaw, M Graham, P Nachev, S Ourselin, ... arXiv preprint arXiv:2002.05692, 2020 | 18 | 2020 |
| A multi-channel uncertainty-aware multi-resolution network for MR to CT synthesis K Klaser, P Borges, R Shaw, M Ranzini, M Modat, D Atkinson, ... Applied sciences 11 (4), 1667, 2021 | 11 | 2021 |
| A heteroscedastic uncertainty model for decoupling sources of MRI image quality R Shaw, CH Sudre, S Ourselin, MJ Cardoso Medical Imaging with Deep Learning, 733-742, 2020 | 10 | 2020 |
| Human gaussian splatting: Real-time rendering of animatable avatars A Moreau, J Song, H Dhamo, R Shaw, Y Zhou, E Pérez-Pellitero arXiv preprint arXiv:2311.17113, 2023 | 9 | 2023 |
| Headgas: Real-time animatable head avatars via 3d gaussian splatting H Dhamo, Y Nie, A Moreau, J Song, R Shaw, Y Zhou, E Pérez-Pellitero arXiv preprint arXiv:2312.02902, 2023 | 4 | 2023 |
| Vschh 2023: A benchmark for the view synthesis challenge of human heads Y Jang, J Zheng, J Song, H Dhamo, E Pérez-Pellitero, T Tanay, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 4 | 2023 |
| Hdr reconstruction from bracketed exposures and events R Shaw, S Catley-Chandar, A Leonardis, E Perez-Pellitero arXiv preprint arXiv:2203.14825, 2022 | 4 | 2022 |
| Uncertainty-aware multi-resolution whole-body MR to CT synthesis K Kläser, P Borges, R Shaw, M Ranzini, M Modat, D Atkinson, ... Simulation and Synthesis in Medical Imaging: 5th International Workshop …, 2020 | 4 | 2020 |
| Acquisition-invariant brain MRI segmentation with informative uncertainties P Borges, R Shaw, T Varsavsky, K Kläser, D Thomas, I Drobnjak, ... Medical Image Analysis 92, 103058, 2024 | 3 | 2024 |
| Estimating MRI image quality via image reconstruction uncertainty R Shaw, CH Sudre, S Ourselin, MJ Cardoso arXiv preprint arXiv:2106.10992, 2021 | 3 | 2021 |
| A decoupled uncertainty model for mri segmentation quality estimation R Shaw, CH Sudre, S Ourselin, MJ Cardoso, HG Pemberton arXiv preprint arXiv:2109.02413, 2021 | 2 | 2021 |
| SWAGS: Sampling Windows Adaptively for Dynamic 3D Gaussian Splatting R Shaw, J Song, A Moreau, M Nazarczuk, S Catley-Chandar, H Dhamo, ... arXiv preprint arXiv:2312.13308, 2023 | 1 | 2023 |
| A Heteroscedastic Uncertainty Model for Decoupling Sources of MRI Image Quality R Shaw, CH Sudre, S Ourselin, MJ Cardoso, HG Pemberton Machine Learning for Biomedical Imaging 1 (MIDL 2020 special issue), 1-23, 2021 | 1 | 2021 |
| The role of MRI physics in brain segmentation CNNs: achieving acquisition invariance and instructive uncertainties P Borges, R Shaw, T Varsavsky, K Klaser, D Thomas, I Drobnjak, ... Simulation and Synthesis in Medical Imaging: 6th International Workshop …, 2021 | 1 | 2021 |
| RoGUENeRF: A Robust Geometry-Consistent Universal Enhancer for NeRF S Catley-Chandar, R Shaw, G Slabaugh, E Perez-Pellitero arXiv preprint arXiv:2403.11909, 2024 | | 2024 |
| MRI Artefact Augmentation: Robust Deep Learning Systems and Automated Quality Control R Shaw UCL (University College London), 2022 | | 2022 |
| OPTICAL MEASUREMENT OF LOW-FREQUENCY VIBRATION R Shaw | | |
