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| Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review J Bernal, K Kushibar, DS Asfaw, S Valverde, A Oliver, R Martí, X Lladó Artificial intelligence in medicine 95, 64-81, 2019 | 427 | 2019 |
| Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach S Valverde, M Cabezas, E Roura, S González-Villà, D Pareto, ... NeuroImage 155, 159-168, 2017 | 376 | 2017 |
| Standardized assessment of automatic segmentation of white matter hyperintensities and results of the WMH segmentation challenge HJ Kuijf, JM Biesbroek, J De Bresser, R Heinen, S Andermatt, M Bento, ... IEEE transactions on medical imaging 38 (11), 2556-2568, 2019 | 273 | 2019 |
| 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 | 245 | 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 | 141 | 2019 |
| A review on brain structures segmentation in magnetic resonance imaging S González-Villà, A Oliver, S Valverde, L Wang, R Zwiggelaar, X Lladó Artificial intelligence in medicine 73, 45-69, 2016 | 132 | 2016 |
| 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 | 120 | 2018 |
| 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 | 113 | 2015 |
| A toolbox for multiple sclerosis lesion segmentation E Roura, A Oliver, M Cabezas, S Valverde, D Pareto, JC Vilanova, ... Neuroradiology 57, 1031-1043, 2015 | 109 | 2015 |
| Acute ischemic stroke lesion core segmentation in CT perfusion images using fully convolutional neural networks A Clerigues, S Valverde, J Bernal, J Freixenet, A Oliver, X Lladó Computers in biology and medicine 115, 103487, 2019 | 103 | 2019 |
| Acute and sub-acute stroke lesion segmentation from multimodal MRI A Clèrigues, S Valverde, J Bernal, J Freixenet, A Oliver, X Lladó Computer methods and programs in biomedicine 194, 105521, 2020 | 79 | 2020 |
| A white matter lesion-filling approach to improve brain tissue volume measurements S Valverde, A Oliver, X Lladó NeuroImage: Clinical 6, 86-92, 2014 | 78 | 2014 |
| Automated tissue segmentation of MR brain images in the presence of white matter lesions S Valverde, A Oliver, E Roura, S González-Villà, D Pareto, JC Vilanova, ... Medical image analysis 35, 446-457, 2017 | 71 | 2017 |
| 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, À Rovira, ... NeuroImage: Clinical 25, 102149, 2020 | 68 | 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, À Rovira, ... NeuroImage: Clinical 17, 607-615, 2018 | 67 | 2018 |
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| Multiple sclerosis lesion synthesis in MRI using an encoder-decoder U-NET M Salem, S Valverde, M Cabezas, D Pareto, A Oliver, J Salvi, À Rovira, ... IEEE Access 7, 25171-25184, 2019 | 59 | 2019 |
| Computational analysis of multimorbidity between asthma, eczema and rhinitis D Aguilar, M Pinart, GH Koppelman, Y Saeys, MC Nawijn, DS Postma, ... PLoS One 12 (6), e0179125, 2017 | 56 | 2017 |
| 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 | 51 | 2019 |
Xavier LladoFull Professor. ICREA Academia. University of Girona.在 eia.udg.edu 的电子邮件经过验证
