| Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation J Wen, E Thibeau-Sutre, M Diaz-Melo, J Samper-González, A Routier, ... Medical image analysis 63, 101694, 2020 | 618 | 2020 |
| Attenuation Correction Synthesis for Hybrid PET-MR Scanners: Application to Brain Studies N Burgos, MJ Cardoso, K Thielemans, M Modat, S Pedemonte, J Dickson, ... Medical Imaging, IEEE Transactions on 33 (12), 2332 - 2341, 2014 | 422 | 2014 |
| 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 | 245 | 2017 |
| Reproducible evaluation of classification methods in Alzheimer's disease: framework and application to MRI and PET data J Samper-González, N Burgos, S Bottani, S Fontanella, P Lu, A Marcoux, ... NeuroImage 183, 504 - 521, 2018 | 208 | 2018 |
| Comparative study of algorithms for synthetic CT generation from MRI: consequences for MRI‐guided radiation planning in the pelvic region H Arabi, JA Dowling, N Burgos, X Han, PB Greer, N Koutsouvelis, H Zaidi Medical physics 45 (11), 5218-5233, 2018 | 134 | 2018 |
| Clinica: an open source software platform for reproducible clinical neuroscience studies A Routier, N Burgos, M Díaz, M Bacci, S Bottani, O El-Rifai, S Fontanella, ... Frontiers in Neuroinformatics 15, 39, 2021 | 122 | 2021 |
| Study protocol: Insight 46–a neuroscience sub-study of the MRC National Survey of Health and Development CA Lane, TD Parker, DM Cash, K Macpherson, E Donnachie, ... BMC neurology 17, 1-25, 2017 | 103 | 2017 |
| Predicting the progression of mild cognitive impairment using machine learning: a systematic, quantitative and critical review M Ansart, S Epelbaum, G Bassignana, A Bône, S Bottani, T Cattai, ... Medical Image Analysis 67, 101848, 2021 | 87 | 2021 |
| Evaluation of a multi-atlas CT synthesis approach for MRI-only radiotherapy treatment planning F Guerreiro, N Burgos, A Dunlop, K Wong, I Petkar, C Nutting, ... Physica Medica 35, 7-17, 2017 | 81 | 2017 |
| Data augmentation in high dimensional low sample size setting using a geometry-based variational autoencoder C Chadebec, E Thibeau-Sutre, N Burgos, S Allassonnière IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (3), 2879-2896, 2022 | 80 | 2022 |
| Attenuation correction synthesis for hybrid PET-MR scanners N Burgos, MJ Cardoso, M Modat, S Pedemonte, J Dickson, A Barnes, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013 | 65 | 2013 |
| Robust CT synthesis for radiotherapy planning: application to the head and neck region N Burgos, MJ Cardoso, F Guerreiro, C Veiga, M Modat, J McClelland, ... Medical Image Computing and Computer-Assisted Intervention--MICCAI 2015 …, 2015 | 60 | 2015 |
| AD Course Map charts Alzheimer’s disease progression I Koval, A Bône, M Louis, T Lartigue, S Bottani, A Marcoux, ... Scientific Reports 11 (1), 8020, 2021 | 58 | 2021 |
| Machine learning for classification and prediction of brain diseases: recent advances and upcoming challenges N Burgos, O Colliot Current Opinion in Neurology 33 (4), 439-450, 2020 | 58 | 2020 |
| Multi-contrast attenuation map synthesis for PET/MR scanners: assessment on FDG and Florbetapir PET tracers N Burgos, MJ Cardoso, K Thielemans, M Modat, J Dickson, JM Schott, ... European journal of nuclear medicine and molecular imaging 42, 1447-1458, 2015 | 54 | 2015 |
| Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning N Burgos, F Guerreiro, J McClelland, B Presles, M Modat, S Nill, ... Physics in Medicine & Biology 62 (11), 4237, 2017 | 51 | 2017 |
| Pilot study of repeated blood-brain barrier disruption in patients with mild Alzheimer’s disease with an implantable ultrasound device S Epelbaum, N Burgos, M Canney, D Matthews, M Houot, MD Santin, ... Alzheimer's Research & Therapy 14 (1), 40, 2022 | 49 | 2022 |
| NiftyWeb: web based platform for image processing on the cloud F Prados Carrasco, MJ Cardoso, N Burgos, CAM Wheeler-Kingshott, ... International Society for Magnetic Resonance in Medicine (ISMRM), 2016 | 44* | 2016 |
| Direct parametric reconstruction with joint motion estimation/correction for dynamic brain PET data J Jiao, A Bousse, K Thielemans, N Burgos, PSJ Weston, JM Schott, ... IEEE transactions on medical imaging 36 (1), 203-213, 2016 | 41 | 2016 |
| Ensemble learning of convolutional neural network, support vector machine, and best linear unbiased predictor for brain age prediction: Aramis contribution to the predictive … B Couvy-Duchesne, J Faouzi, B Martin, E Thibeau–Sutre, A Wild, ... Frontiers in Psychiatry 11, 593336, 2020 | 40 | 2020 |
Olivier ColliotResearch Director at CNRS, ARAMIS LabEmail verificata su cnrs.fr