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 | 1941 | 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 | 326 | 2017 |
Automatic segmentation and volumetry of multiple sclerosis brain lesions from MR images S Jain, DM Sima, A Ribbens, M Cambron, A Maertens, W Van Hecke, ... NeuroImage: Clinical 8, 367-375, 2015 | 260 | 2015 |
An automated quantitation of short echo time MRS spectra in an open source software environment: AQSES JB Poullet, DM Sima, AW Simonetti, B De Neuter, L Vanhamme, ... NMR in Biomedicine: An International Journal Devoted to the Development and …, 2007 | 187 | 2007 |
MRS signal quantitation: a review of time-and frequency-domain methods JB Poullet, DM Sima, S Van Huffel Journal of Magnetic Resonance 195 (2), 134-144, 2008 | 179 | 2008 |
Regularized total least squares based on quadratic eigenvalue problem solvers DM Sima, S Van Huffel, GH Golub BIT Numerical Mathematics 44, 793-812, 2004 | 146 | 2004 |
Integrating diffusion kurtosis imaging, dynamic susceptibility-weighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomas S Van Cauter, F De Keyzer, DM Sima, A Croitor Sava, F D'Arco, J Veraart, ... Neuro-oncology 16 (7), 1010-1021, 2014 | 109 | 2014 |
Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI N Sauwen, M Acou, S Van Cauter, DM Sima, J Veraart, F Maes, ... NeuroImage: Clinical 12, 753-764, 2016 | 89 | 2016 |
Reliable measurements of brain atrophy in individual patients with multiple sclerosis D Smeets, A Ribbens, DM Sima, M Cambron, D Horakova, S Jain, ... Brain and behavior 6 (9), e00518, 2016 | 78 | 2016 |
Machine learning approach for classifying multiple sclerosis courses by combining clinical data with lesion loads and magnetic resonance metabolic features A Ion-Mărgineanu, G Kocevar, C Stamile, DM Sima, F Durand-Dubief, ... Frontiers in neuroscience 11, 398, 2017 | 72 | 2017 |
Measurement of whole-brain and gray matter atrophy in multiple sclerosis: assessment with MR imaging L Storelli, MA Rocca, E Pagani, W Van Hecke, MA Horsfield, ... Radiology 288 (2), 554-564, 2018 | 64 | 2018 |
Automatic quantification of computed tomography features in acute traumatic brain injury S Jain, TV Vyvere, V Terzopoulos, DM Sima, E Roura, A Maas, G Wilms, ... Journal of neurotrauma 36 (11), 1794-1803, 2019 | 63 | 2019 |
Regularization techniques in model fitting and parameter estimation DM Sima Diss. KU Leuven, 2006 | 55 | 2006 |
Hierarchical non‐negative matrix factorization (hNMF): a tissue pattern differentiation method for glioblastoma multiforme diagnosis using MRSI Y Li, DM Sima, SV Cauter, AR Croitor Sava, U Himmelreich, Y Pi, ... NMR in Biomedicine 26 (3), 307-319, 2013 | 54 | 2013 |
Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization N Sauwen, M Acou, DM Sima, J Veraart, F Maes, U Himmelreich, ... BMC medical imaging 17, 1-14, 2017 | 53 | 2017 |
Separable nonlinear least squares fitting with linear bound constraints and its application in magnetic resonance spectroscopy data quantification DM Sima, S Van Huffel Journal of computational and applied mathematics 203 (1), 264-278, 2007 | 48 | 2007 |
The Total Least Squares Problem in : A New Classification with the Relationship to the Classical Works I Hnětynková, M Plešinger, DM Sima, Z Strakoš, S Van Huffel SIAM Journal on Matrix Analysis and Applications 32 (3), 748-770, 2011 | 46 | 2011 |
Hierarchical non‐negative matrix factorization to characterize brain tumor heterogeneity using multi‐parametric MRI N Sauwen, DM Sima, S Van Cauter, J Veraart, A Leemans, F Maes, ... NMR in Biomedicine 28 (12), 1599-1624, 2015 | 44 | 2015 |
Automated MRI volumetry as a diagnostic tool for Alzheimer's disease: Validation of icobrain dm H Struyfs, DM Sima, M Wittens, A Ribbens, NP de Barros, T Vân Phan, ... NeuroImage: Clinical 26, 102243, 2020 | 43 | 2020 |
Two time point MS lesion segmentation in brain MRI: an expectation-maximization framework S Jain, A Ribbens, DM Sima, M Cambron, J De Keyser, C Wang, ... Frontiers in neuroscience 10, 576, 2016 | 43 | 2016 |