| 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 | 2159 | 2018 |
| 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 | 492 | 2019 |
| Data preparation for artificial intelligence in medical imaging: A comprehensive guide to open-access platforms and tools O Diaz, K Kushibar, R Osuala, A Linardos, L Garrucho, L Igual, P Radeva, ... Physica medica 83, 25-37, 2021 | 134 | 2021 |
| 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 | 128 | 2020 |
| 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 | 128 | 2018 |
| FUTURE-AI: guiding principles and consensus recommendations for trustworthy artificial intelligence in medical imaging K Lekadir, R Osuala, C Gallin, N Lazrak, K Kushibar, G Tsakou, S Aussó, ... arXiv preprint arXiv:2109.09658, 2021 | 88 | 2021 |
| Federated learning for multi-center imaging diagnostics: a simulation study in cardiovascular disease A Linardos, K Kushibar, S Walsh, P Gkontra, K Lekadir Scientific Reports 12 (1), 3551, 2022 | 78 | 2022 |
| Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging R Osuala, K Kushibar, L Garrucho, A Linardos, Z Szafranowska, S Klein, ... Medical Image Analysis 84, 102704, 2023 | 68* | 2023 |
| 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 |
| Deep learning segmentation of the right ventricle in cardiac MRI: the M&Ms challenge C Martín-Isla, VM Campello, C Izquierdo, K Kushibar, C Sendra-Balcells, ... IEEE Journal of Biomedical and Health Informatics 27 (7), 3302-3313, 2023 | 51 | 2023 |
| 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 | 50 | 2019 |
| Domain generalization in deep learning-based mass detection in mammography: A large-scale multi-center study L Garrucho, K Kushibar, S Jouide, O Diaz, L Igual, K Lekadir Artificial Intelligence in Medicine 132 (102386), 2022 | 39 | 2022 |
| Survival prediction using ensemble tumor segmentation and transfer learning M Cabezas, S Valverde, S González-Villà, A Clérigues, M Salem, ... arXiv preprint arXiv:1810.04274, 2018 | 32 | 2018 |
| Face recognition using artificial neural networks in parallel architecture B Omarov, A Suliman, K Kushibar Asian Research Publishing Network, 2016 | 29 | 2016 |
| medigan: a Python library of pretrained generative models for medical image synthesis R Osuala, G Skorupko, N Lazrak, L Garrucho, E García, S Joshi, S Jouide, ... Journal of Medical Imaging 10 (6), 061403-061403, 2023 | 28* | 2023 |
| FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare K Lekadir, AF Frangi, AR Porras, B Glocker, C Cintas, CP Langlotz, ... bmj 388, 2025 | 27 | 2025 |
| High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection L Garrucho, K Kushibar, R Osuala, O Diaz, A Catanese, J Del Riego, ... Frontiers in Oncology 12, 1044496, 2023 | 19 | 2023 |
| Layer ensembles: A single-pass uncertainty estimation in deep learning for segmentation K Kushibar, V Campello, L Garrucho, A Linardos, P Radeva, K Lekadir International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 18 | 2022 |
| Generating longitudinal atrophy evaluation datasets on brain magnetic resonance images using convolutional neural networks and segmentation priors J Bernal, S Valverde, K Kushibar, M Cabezas, A Oliver, X Llado, ... Neuroinformatics 19, 477-492, 2021 | 17 | 2021 |
| Transductive transfer learning for domain adaptation in brain magnetic resonance image segmentation K Kushibar, M Salem, S Valverde, À Rovira, J Salvi, A Oliver, X Lladó Frontiers in Neuroscience 15, 608808, 2021 | 13 | 2021 |
Karim LekadirICREA Research Professor, Universitat de BarcelonaAdresse e-mail validée de ub.edu