|Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations|
CH Sudre, W Li, T Vercauteren, S Ourselin, MJ Cardoso
Deep learning in medical image analysis and multimodal learning for clinical …, 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
|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
|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
|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
|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
|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
|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
|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
|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
|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
|Accurate multimodal probabilistic prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment|
J Young, M Modat, MJ Cardoso, A Mendelson, D Cash, S Ourselin, ...
NeuroImage: Clinical 2, 735-745, 2013
|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
International conference on information processing in medical imaging, 348-360, 2017
|A comparison of voxel and surface based cortical thickness estimation methods|
MJ Clarkson, MJ Cardoso, GR Ridgway, M Modat, KK Leung, JD Rohrer, ...
Neuroimage 57 (3), 856-865, 2011
|Neurofilament light chain: a biomarker for genetic frontotemporal dementia|
LH Meeter, EG Dopper, LC Jiskoot, R Sanchez‐Valle, C Graff, L Benussi, ...
Annals of clinical and translational neurology 3 (8), 623-636, 2016
|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
|Right ventricle segmentation from cardiac MRI: a collation study|
C Petitjean, MA Zuluaga, W Bai, JN Dacher, D Grosgeorge, J Caudron, ...
Medical image analysis 19 (1), 187-202, 2015
|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
|Longitudinal multiple sclerosis lesion segmentation: resource and challenge|
A Carass, S Roy, A Jog, JL Cuzzocreo, E Magrath, A Gherman, J Button, ...
NeuroImage 148, 77-102, 2017
|A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients|
CN Ladefoged, I Law, U Anazodo, KS Lawrence, D Izquierdo-Garcia, ...
Neuroimage 147, 346-359, 2017