| Fully automated, quality-controlled cardiac analysis from CMR: validation and large-scale application to characterize cardiac function B Ruijsink, E Puyol-Antón, I Oksuz, M Sinclair, W Bai, JA Schnabel, ... Cardiovascular Imaging 13 (3), 684-695, 2020 | 180 | 2020 |
| Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning I Oksuz, B Ruijsink, E Puyol-Antón, JR Clough, G Cruz, A Bustin, C Prieto, ... Medical image analysis 55, 136-147, 2019 | 120 | 2019 |
| Fairness in cardiac MR image analysis: an investigation of bias due to data imbalance in deep learning based segmentation E Puyol-Antón, B Ruijsink, SK Piechnik, S Neubauer, SE Petersen, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 87 | 2021 |
| Global and local interpretability for cardiac MRI classification JR Clough, I Oksuz, E Puyol-Antón, B Ruijsink, AP King, JA Schnabel International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 79 | 2019 |
| Deep learning-based detection and correction of cardiac MR motion artefacts during reconstruction for high-quality segmentation I Oksuz, JR Clough, B Ruijsink, EP Anton, A Bustin, G Cruz, C Prieto, ... IEEE Transactions on Medical Imaging 39 (12), 4001-4010, 2020 | 74 | 2020 |
| Fairness in cardiac magnetic resonance imaging: assessing sex and racial bias in deep learning-based segmentation E Puyol-Antón, B Ruijsink, J Mariscal Harana, SK Piechnik, S Neubauer, ... Frontiers in cardiovascular medicine 9, 859310, 2022 | 56 | 2022 |
| Automated quantification of myocardial tissue characteristics from native T1 mapping using neural networks with uncertainty-based quality-control E Puyol-Antón, B Ruijsink, CF Baumgartner, M Sinclair, E Konukoglu, ... Journal of Cardiovascular Magnetic Resonance 22, 60-75, 2020 | 40 | 2020 |
| Interpretable deep models for cardiac resynchronisation therapy response prediction E Puyol-Antón, C Chen, JR Clough, B Ruijsink, BS Sidhu, J Gould, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 40 | 2020 |
| Detection and correction of cardiac MRI motion artefacts during reconstruction from k-space I Oksuz, J Clough, B Ruijsink, E Puyol-Antón, A Bustin, G Cruz, C Prieto, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 40 | 2019 |
| A multimodal spatiotemporal cardiac motion atlas from MR and ultrasound data E Puyol-Anton, M Sinclair, B Gerber, MS Amzulescu, H Langet, ... Medical image analysis 40, 96-110, 2017 | 40* | 2017 |
| Regional multi-view learning for cardiac motion analysis: Application to identification of dilated cardiomyopathy patients E Puyol-Antón, B Ruijsink, B Gerber, MS Amzulescu, H Langet, ... IEEE Transactions on Biomedical Engineering 66 (4), 956-966, 2018 | 38 | 2018 |
| Fully automated myocardial strain estimation from cine MRI using convolutional neural networks E Puyol-Antón, B Ruijsink, W Bai, H Langet, M De Craene, JA Schnabel, ... 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 36 | 2018 |
| Medical image computing and computer assisted intervention–MICCAI 2021 E Puyol-Antón, B Ruijsink, SK Piechnik, S Neubauer, SE Petersen, ... Springer International Publishing, Cham, 2021 | 35 | 2021 |
| Deep learning using K-space based data augmentation for automated cardiac MR motion artefact detection I Oksuz, B Ruijsink, E Puyol-Antón, A Bustin, G Cruz, C Prieto, D Rueckert, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 34 | 2018 |
| Fully automated segmentation-based respiratory motion correction of multiplanar cardiac magnetic resonance images for large-scale datasets M Sinclair, W Bai, E Puyol-Antón, O Oktay, D Rueckert, AP King Medical Image Computing and Computer-Assisted Intervention− MICCAI 2017 …, 2017 | 34 | 2017 |
| Artificial intelligence in cardiac MRI: is clinical adoption forthcoming? A Fotaki, E Puyol-Antón, A Chiribiri, R Botnar, K Pushparajah, C Prieto Frontiers in Cardiovascular Medicine 8, 818765, 2022 | 31 | 2022 |
| Prevalence and disease expression of pathogenic and likely pathogenic variants associated with inherited cardiomyopathies in the general population M Bourfiss, M Van Vugt, AI Alasiri, B Ruijsink, J Van Setten, AF Schmidt, ... Circulation: Genomic and Precision Medicine 15 (6), e003704, 2022 | 28 | 2022 |
| A multimodal deep learning model for cardiac resynchronisation therapy response prediction E Puyol-Antón, BS Sidhu, J Gould, B Porter, MK Elliott, V Mehta, ... Medical image analysis 79, 102465, 2022 | 26 | 2022 |
| Probabilistic 3D surface reconstruction from sparse MRI information K Tóthová, S Parisot, M Lee, E Puyol-Antón, A King, M Pollefeys, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 21 | 2020 |
| Uncertainty quantification in CNN-based surface prediction using shape priors K Tóthová, S Parisot, MCH Lee, E Puyol-Antón, LM Koch, AP King, ... Shape in Medical Imaging: International Workshop, ShapeMI 2018, Held in …, 2018 | 20 | 2018 |
Andrew P KingKing's College LondonVerified email at kcl.ac.uk
