| 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 | 2132 | 2018 |
| A review of atlas-based segmentation for magnetic resonance brain images M Cabezas, A Oliver, X Lladó, J Freixenet, MB Cuadra Computer methods and programs in biomedicine 104 (3), e158-e177, 2011 | 581 | 2011 |
| Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach S Valverde, M Cabezas, E Roura, S Gonzįlez-Villą, D Pareto, ... NeuroImage 155, 159-168, 2017 | 400 | 2017 |
| Segmentation of multiple sclerosis lesions in brain MRI: a review of automated approaches X Lladó, A Oliver, M Cabezas, J Freixenet, JC Vilanova, A Quiles, L Valls, ... Information Sciences 186 (1), 164-185, 2012 | 310 | 2012 |
| Objective evaluation of multiple sclerosis lesion segmentation using a data management and processing infrastructure O Commowick, A Istace, M Kain, B Laurent, F Leray, M Simon, SC Pop, ... Scientific reports 8 (1), 13650, 2018 | 282 | 2018 |
| One-shot domain adaptation in multiple sclerosis lesion segmentation using convolutional neural networks S Valverde, M Salem, M Cabezas, D Pareto, JC Vilanova, ... NeuroImage: Clinical 21, 101638, 2019 | 159 | 2019 |
| Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features K Kushibar, S Valverde, S Gonzalez-Villa, J Bernal, M Cabezas, A Oliver, ... Medical image analysis 48, 177-186, 2018 | 127 | 2018 |
| Improving the detection of autism spectrum disorder by combining structural and functional MRI information M Rakić, M Cabezas, K Kushibar, A Oliver, X Lladó NeuroImage: Clinical 25, 102181, 2020 | 124 | 2020 |
| Deep learning in forestry using uav-acquired rgb data: A practical review Y Diez, S Kentsch, M Fukuda, MLL Caceres, K Moritake, M Cabezas Remote Sensing 13 (14), 2837, 2021 | 117 | 2021 |
| A toolbox for multiple sclerosis lesion segmentation E Roura, A Oliver, M Cabezas, S Valverde, D Pareto, JC Vilanova, ... Neuroradiology 57, 1031-1043, 2015 | 115 | 2015 |
| Comparison of 10 brain tissue segmentation methods using revisited IBSR annotations S Valverde, A Oliver, M Cabezas, E Roura, X Lladó Journal of Magnetic Resonance Imaging 41 (1), 93-101, 2015 | 115 | 2015 |
| A fully convolutional neural network for new T2-w lesion detection in multiple sclerosis M Salem, S Valverde, M Cabezas, D Pareto, A Oliver, J Salvi, Ą Rovira, ... NeuroImage: Clinical 25, 102149, 2020 | 76 | 2020 |
| A supervised framework with intensity subtraction and deformation field features for the detection of new T2-w lesions in multiple sclerosis M Salem, M Cabezas, S Valverde, D Pareto, A Oliver, J Salvi, Ą Rovira, ... NeuroImage: Clinical 17, 607-615, 2018 | 72 | 2018 |
| Multiple sclerosis lesion synthesis in MRI using an encoder-decoder U-NET M Salem, S Valverde, M Cabezas, D Pareto, A Oliver, J Salvi, Ą Rovira, ... IEEE Access 7, 25171-25184, 2019 | 68 | 2019 |
| Automatic multiple sclerosis lesion detection in brain MRI by FLAIR thresholding M Cabezas, A Oliver, E Roura, J Freixenet, JC Vilanova, ... Computer methods and programs in biomedicine 115 (3), 147-161, 2014 | 67 | 2014 |
| A. Rovira, A. Oliver, and X. Lladó,“Improving automated multiple sclerosis lesion segmentation with a cascaded 3d convolutional neural network approach,” S Valverde, M Cabezas, E Roura, S Gonzįlez-Villa, D Pareto, ... NeuroImage 155, 159-168, 2017 | 61 | 2017 |
| MARGA: multispectral adaptive region growing algorithm for brain extraction on axial MRI E Roura, A Oliver, M Cabezas, JC Vilanova, A Rovira, L Ramio-Torrenta, ... Computer methods and programs in biomedicine 113 (2), 655-673, 2014 | 58 | 2014 |
| Quantitative analysis of patch-based fully convolutional neural networks for tissue segmentation on brain magnetic resonance imaging J Bernal, K Kushibar, M Cabezas, S Valverde, A Oliver, X Lladó IEEE Access 7, 89986-90002, 2019 | 55 | 2019 |
| QU-BraTS: MICCAI BraTS 2020 challenge on quantifying uncertainty in brain tumor segmentation-analysis of ranking scores and benchmarking results R Mehta, A Filos, U Baid, C Sako, R McKinley, M Rebsamen, K Dätwyler, ... The journal of machine learning for biomedical imaging 2022, 2022 | 51 | 2022 |
| Supervised domain adaptation for automatic sub-cortical brain structure segmentation with minimal user interaction K Kushibar, S Valverde, S Gonzalez-Villa, J Bernal, M Cabezas, A Oliver, ... Scientific reports 9 (1), 6742, 2019 | 49 | 2019 |
Arnau OliverUniversitat de GironaVerified email at eia.udg.edu
