| Multimodal MR synthesis via modality-invariant latent representation A Chartsias, T Joyce, MV Giuffrida, SA Tsaftaris IEEE transactions on medical imaging 37 (3), 803-814, 2017 | 295 | 2017 |
| Adversarial image synthesis for unpaired multi-modal cardiac data A Chartsias, T Joyce, R Dharmakumar, SA Tsaftaris Simulation and Synthesis in Medical Imaging: Second International Workshop …, 2017 | 232 | 2017 |
| Disentangled representation learning in cardiac image analysis A Chartsias, T Joyce, G Papanastasiou, S Semple, M Williams, DE Newby, ... Medical image analysis 58, 101535, 2019 | 167 | 2019 |
| Analysis of individual mouse activity in group housed animals of different inbred strains using a novel automated home cage analysis system RS Bains, HL Cater, RR Sillito, A Chartsias, D Sneddon, D Concas, ... Frontiers in behavioral neuroscience 10, 106, 2016 | 126 | 2016 |
| Factorised spatial representation learning: Application in semi-supervised myocardial segmentation A Chartsias, T Joyce, G Papanastasiou, S Semple, M Williams, D Newby, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 78 | 2018 |
| Automated recording of home cage activity and temperature of individual rats housed in social groups: The Rodent Big Brother project WS Redfern, K Tse, C Grant, A Keerie, DJ Simpson, JC Pedersen, ... PloS one 12 (9), e0181068, 2017 | 74 | 2017 |
| Disentangle, align and fuse for multimodal and semi-supervised image segmentation A Chartsias, G Papanastasiou, C Wang, S Semple, DE Newby, ... IEEE transactions on medical imaging 40 (3), 781-792, 2020 | 70 | 2020 |
| Robust multi-modal MR image synthesis T Joyce, A Chartsias, SA Tsaftaris Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 66 | 2017 |
| Pseudo-healthy synthesis with pathology disentanglement and adversarial learning T Xia, A Chartsias, SA Tsaftaris Medical Image Analysis 64, 101719, 2020 | 52 | 2020 |
| Learning to synthesise the ageing brain without longitudinal data T Xia, A Chartsias, C Wang, SA Tsaftaris, ... Medical Image Analysis 73, 102169, 2021 | 45 | 2021 |
| Deep multi-class segmentation without ground-truth labels T Joyce, A Chartsias, SA Tsaftaris Medical imaging with deep learning, 2018 | 44 | 2018 |
| Consistent brain ageing synthesis T Xia, A Chartsias, SA Tsaftaris, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 29 | 2019 |
| Automated echocardiographic detection of heart failure with preserved ejection fraction using artificial intelligence AP Akerman, M Porumb, CG Scott, A Beqiri, A Chartsias, AJ Ryu, ... JACC: Advances 2 (6), 100452, 2023 | 27 | 2023 |
| International workshop on simulation and synthesis in medical imaging A Chartsias, T Joyce, R Dharmakumar, SA Tsaftaris Springer, 2017 | 22 | 2017 |
| Disentangled representations for domain-generalized cardiac segmentation X Liu, S Thermos, A Chartsias, A O’Neil, SA Tsaftaris Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC …, 2021 | 20 | 2021 |
| FIRE: unsupervised bi-directional inter-modality registration using deep networks C Wang, G Papanastasiou, A Chartsias, G Jacenkow, SA Tsaftaris, ... arXiv preprint arXiv:1907.05062, 2019 | 16 | 2019 |
| Adversarial pseudo healthy synthesis needs pathology factorization T Xia, A Chartsias, SA Tsaftaris arXiv preprint arXiv:1901.07295, 2019 | 16 | 2019 |
| Measuring the biases and effectiveness of content-style disentanglement X Liu, S Thermos, G Valvano, A Chartsias, A O'Neil, SA Tsaftaris arXiv preprint arXiv:2008.12378, 2020 | 15 | 2020 |
| Multimodal cardiac segmentation using disentangled representation learning A Chartsias, G Papanastasiou, C Wang, C Stirrat, S Semple, D Newby, ... Statistical Atlases and Computational Models of the Heart. Multi-Sequence …, 2020 | 13 | 2020 |
| CRISP - Reliable Uncertainty Estimation for Medical Image Segmentation T Judge, O Bernard, M Porumb, A Chartsias, A Beqiri, PM Jodoin International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 12 | 2022 |
