| Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study LH Nguyen, DA Drew, MS Graham, AD Joshi, CG Guo, W Ma, RS Mehta, ... The Lancet Public Health 5 (9), e475-e483, 2020 | 2131 | 2020 |
| Attributes and predictors of long COVID CH Sudre, B Murray, T Varsavsky, MS Graham, RS Penfold, RC Bowyer, ... Nature medicine 27 (4), 626-631, 2021 | 1793 | 2021 |
| Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations CH Sudre, W Li, T Vercauteren, S Ourselin, M Jorge Cardoso Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017 | 1760 | 2017 |
| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 1358 | 2018 |
| Real-time tracking of self-reported symptoms to predict potential COVID-19 C Menni, AM Valdes, MB Freidin, CH Sudre, LH Nguyen, DA Drew, ... Nature medicine 26 (7), 1037-1040, 2020 | 1323 | 2020 |
| The future of digital health with federated learning N Rieke, J Hancox, W Li, F Milletari, HR Roth, S Albarqouni, S Bakas, ... NPJ digital medicine 3 (1), 119, 2020 | 820 | 2020 |
| A large annotated medical image dataset for the development and evaluation of segmentation algorithms AL Simpson, M Antonelli, S Bakas, M Bilello, K Farahani, B Van Ginneken, ... arXiv preprint arXiv:1902.09063, 2019 | 644 | 2019 |
| The liver tumor segmentation benchmark (lits) P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical Image Analysis 84, 102680, 2023 | 608 | 2023 |
| NiftyNet: a deep-learning platform for medical imaging E Gibson, W Li, C Sudre, L Fidon, DI Shakir, G Wang, Z Eaton-Rosen, ... Computer methods and programs in biomedicine 158, 113-122, 2018 | 595 | 2018 |
| Presymptomatic cognitive and neuroanatomical changes in genetic frontotemporal dementia in the Genetic Frontotemporal dementia Initiative (GENFI) study: a cross-sectional analysis JD Rohrer, JM Nicholas, DM Cash, J Van Swieten, E Dopper, L Jiskoot, ... The Lancet Neurology 14 (3), 253-262, 2015 | 500 | 2015 |
| Faciobrachial dystonic seizures: the influence of immunotherapy on seizure control and prevention of cognitive impairment in a broadening phenotype SR Irani, CJ Stagg, JM Schott, CR Rosenthal, SA Schneider, P Pettingill, ... Brain 136 (10), 3151-3162, 2013 | 427 | 2013 |
| Rapid implementation of mobile technology for real-time epidemiology of COVID-19 DA Drew, LH Nguyen, CJ Steves, C Menni, M Freydin, T Varsavsky, ... Science 368 (6497), 1362-1367, 2020 | 377 | 2020 |
| Serum neurofilament light chain protein is a measure of disease intensity in frontotemporal dementia JD Rohrer, IOC Woollacott, KM Dick, E Brotherhood, E Gordon, A Fellows, ... Neurology 87 (13), 1329-1336, 2016 | 367 | 2016 |
| Geodesic information flows: spatially-variant graphs and their application to segmentation and fusion MJ Cardoso, M Modat, R Wolz, A Melbourne, D Cash, D Rueckert, ... IEEE transactions on medical imaging 34 (9), 1976-1988, 2015 | 355 | 2015 |
| Attenuation correction synthesis for hybrid PET-MR scanners: application to brain studies N Burgos, MJ Cardoso, K Thielemans, M Modat, S Pedemonte, J Dickson, ... IEEE transactions on medical imaging 33 (12), 2332-2341, 2014 | 354 | 2014 |
| Privacy-preserving federated brain tumour segmentation W Li, F Milletarì, D Xu, N Rieke, J Hancox, W Zhu, M Baust, Y Cheng, ... Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019 …, 2019 | 349 | 2019 |
| On the compactness, efficiency, and representation of 3D convolutional networks: brain parcellation as a pretext task W Li, G Wang, L Fidon, S Ourselin, MJ Cardoso, T Vercauteren Information Processing in Medical Imaging: 25th International Conference …, 2017 | 329 | 2017 |
| Deep gray matter volume loss drives disability worsening in multiple sclerosis A Eshaghi, F Prados, WJ Brownlee, DR Altmann, C Tur, MJ Cardoso, ... Annals of neurology 83 (2), 210-222, 2018 | 314 | 2018 |
| STEPS: Similarity and Truth Estimation for Propagated Segmentations and its application to hippocampal segmentation and brain parcelation MJ Cardoso, K Leung, M Modat, S Keihaninejad, D Cash, J Barnes, ... Medical image analysis 17 (6), 671-684, 2013 | 283 | 2013 |
| Progression of regional grey matter atrophy in multiple sclerosis A Eshaghi, RV Marinescu, AL Young, NC Firth, F Prados, ... Brain 141 (6), 1665-1677, 2018 | 268 | 2018 |
Sebastien OurselinProfessor of Healthcare Engineering, King's College LondonBestätigte E-Mail-Adresse bei kcl.ac.uk
