| 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 | 92 | 2018 |
| Image quality transfer and applications in diffusion MRI DC Alexander, D Zikic, A Ghosh, R Tanno, V Wottschel, J Zhang, E Kaden, ... NeuroImage 152, 283-298, 2017 | 61 | 2017 |
| Predicting outcome in clinically isolated syndrome using machine learning V Wottschel, DC Alexander, PP Kwok, DT Chard, ML Stromillo, ... NeuroImage: Clinical 7, 281-287, 2015 | 46 | 2015 |
| Gray matter MRI differentiates neuromyelitis optica from multiple sclerosis using random forest A Eshaghi, V Wottschel, R Cortese, M Calabrese, MA Sahraian, ... Neurology 87 (23), 2463-2470, 2016 | 32 | 2016 |
| MRI predictors of amyloid pathology: results from the EMIF-AD Multimodal Biomarker Discovery study M Ten Kate, A Redolfi, E Peira, I Bos, SJ Vos, R Vandenberghe, S Gabel, ... Alzheimer's research & therapy 10 (1), 1-12, 2018 | 28 | 2018 |
| Localization of the epileptogenic zone using interictal MEG and machine learning in a large cohort of drug-resistant epilepsy patients IA Nissen, CJ Stam, ECW van Straaten, V Wottschel, JC Reijneveld, ... Frontiers in neurology 9, 647, 2018 | 13 | 2018 |
| MRI-based prediction of conversion from clinically isolated syndrome to clinically definite multiple sclerosis using SVM and lesion geometry K Bendfeldt, B Taschler, L Gaetano, P Madoerin, P Kuster, ... Brain imaging and behavior 13 (5), 1361-1374, 2019 | 8 | 2019 |
| SVM recursive feature elimination analyses of structural brain MRI predicts near-term relapses in patients with clinically isolated syndromes suggestive of multiple sclerosis V Wottschel, DT Chard, C Enzinger, M Filippi, JL Frederiksen, C Gasperini, ... NeuroImage: Clinical 24, 102011, 2019 | 8 | 2019 |
| ExploreASL: an image processing pipeline for multi-center ASL perfusion MRI studies HJMM Mutsaerts, J Petr, P Groot, P Vandemaele, S Ingala, AD Robertson, ... NeuroImage 219, 117031, 2020 | 7 | 2020 |
| Multi-study validation of data-driven disease progression models to characterize evolution of biomarkers in Alzheimer's disease D Archetti, S Ingala, V Venkatraghavan, V Wottschel, AL Young, M Bellio, ... NeuroImage: Clinical 24, 101954, 2019 | 6 | 2019 |
| Multitracer model for staging cortical amyloid deposition using PET imaging LE Collij, F Heeman, G Salvadó, S Ingala, D Altomare, A de Wilde, ... Neurology 95 (11), e1538-e1553, 2020 | 3 | 2020 |
| Reduced accuracy of MRI deep grey matter segmentation in multiple sclerosis: an evaluation of four automated methods against manual reference segmentations in a multi-center cohort A de Sitter, T Verhoeven, J Burggraaff, Y Liu, J Simoes, S Ruggieri, ... Journal of neurology 267 (12), 3541-3554, 2020 | 2 | 2020 |
| P2‐445: EVENT‐BASED MODELING OF THE TEMPORAL ORDERING OF REGIONAL β‐AMYLOID DEPOSITION IN THE BRAIN IL Alves, L Collij, F Heeman, V Wottschel, E Konijnenberg, A den Braber, ... Alzheimer's & Dementia 14 (7S_Part_16), P887-P888, 2018 | 2 | 2018 |
| Studying the extracellular contribution to the double wave vector diffusion-weighted signal P Ulloa, V Wottschel, MA Koch Current Directions in Biomedical Engineering 1 (1), 240-244, 2015 | 2 | 2015 |
| Prediction of second neurological attack in patients with clinically isolated syndrome using support vector machines V Wottschel, O Ciccarelli, DT Chard, DH Miller, DC Alexander 2013 International Workshop on Pattern Recognition in Neuroimaging, 82-85, 2013 | 2 | 2013 |
| The relation between APOE genotype and cerebral microbleeds in cognitively unimpaired middle-and old-aged individuals S Ingala, L Mazzai, CH Sudre, G Salvadó, A Brugulat-Serrat, V Wottschel, ... Neurobiology of Aging 95, 104-114, 2020 | 1 | 2020 |
| Supervised machine learning in multiple sclerosis: applications to clinically isolated syndromes V Wottschel UCL (University College London), 2017 | 1 | 2017 |
| P1‐009: A Data‐Driven Comparison of the Progression of Brain Atrophy in Posterior Cortical Atrophy and Alzheimer's Disease RV Marinescu, AL Young, NP Oxtoby, NC Firth, M Lorenzi, A Eshaghi, ... Alzheimer's & Dementia 12, P401-P402, 2016 | 1 | 2016 |
| Prediction of Second Clinical Attack in CIS patients using SVMs V Wottschel, DC Alexander, DT Chard, DH Miller, O Ciccarelli Magnetic Resonance Materials in Physics, Biology and Medicine 26 (1), 262-263, 2013 | 1 | 2013 |
| Predicting clinical conversion to multiple sclerosis in patients with clinically isolated syndrome using machine learning techniques O Ciccarelli, PP Kwok, V Wottschel, D Chard, ML Stromillo, N De Stefano, ... MULTIPLE SCLEROSIS JOURNAL 18, 30-31, 2012 | 1 | 2012 |
Daniel C. AlexanderProfessor of Imaging Science, Centre for Medical Image Computing, Department of Computer ScienceVerified email at cs.ucl.ac.uk
