| 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 | 2146 | 2018 |
| A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study R Sun, EJ Limkin, M Vakalopoulou, L Dercle, S Champiat, SR Han, ... The Lancet Oncology 19 (9), 1180-1191, 2018 | 1055 | 2018 |
| Building detection in very high resolution multispectral data with deep learning features M Vakalopoulou, K Karantzalos, N Komodakis, N Paragios 2015 IEEE international geoscience and remote sensing symposium (IGARSS …, 2015 | 363 | 2015 |
| Standardization of brain MR images across machines and protocols: bridging the gap for MRI-based radiomics A Carré, G Klausner, M Edjlali, M Lerousseau, J Briend-Diop, R Sun, ... Scientific reports 10 (1), 12340, 2020 | 231 | 2020 |
| Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning A Hering, L Hansen, TCW Mok, ACS Chung, H Siebert, S Häger, A Lange, ... IEEE Transactions on Medical Imaging 42 (3), 697-712, 2022 | 204 | 2022 |
| AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia G Chassagnon, M Vakalopoulou, E Battistella, S Christodoulidis, ... Medical image analysis 67, 101860, 2021 | 198* | 2021 |
| Artificial intelligence applications for thoracic imaging G Chassagnon, M Vakalopoulou, N Paragios, MP Revel European journal of radiology 123, 108774, 2020 | 181 | 2020 |
| Demystification of AI-driven medical image interpretation: past, present and future P Savadjiev, J Chong, A Dohan, M Vakalopoulou, C Reinhold, ... European radiology 29, 1616-1624, 2019 | 175 | 2019 |
| Trastuzumab deruxtecan in metastatic breast cancer with variable HER2 expression: the phase 2 DAISY trial F Mosele, E Deluche, A Lusque, L Le Bescond, T Filleron, Y Pradat, ... Nature medicine 29 (8), 2110-2120, 2023 | 165 | 2023 |
| Detecting urban changes with recurrent neural networks from multitemporal Sentinel-2 data M Papadomanolaki, S Verma, M Vakalopoulou, S Gupta, K Karantzalos IGARSS 2019-2019 IEEE international geoscience and remote sensing symposium …, 2019 | 164 | 2019 |
| A deep multitask learning framework coupling semantic segmentation and fully convolutional LSTM networks for urban change detection M Papadomanolaki, M Vakalopoulou, K Karantzalos IEEE Transactions on Geoscience and Remote Sensing 59 (9), 7651-7668, 2021 | 131 | 2021 |
| Weakly supervised multiple instance learning histopathological tumor segmentation M Lerousseau, M Vakalopoulou, M Classe, J Adam, E Battistella, A Carré, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 111 | 2020 |
| Deep learning: definition and perspectives for thoracic imaging G Chassagnon, M Vakalopolou, N Paragios, MP Revel European radiology 30, 2021-2030, 2020 | 102 | 2020 |
| Atlasnet: Multi-atlas non-linear deep networks for medical image segmentation M Vakalopoulou, G Chassagnon, N Bus, R Marini, EI Zacharaki, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 87 | 2018 |
| Multitemporal very high resolution from space: Outcome of the 2016 IEEE GRSS data fusion contest L Mou, X Zhu, M Vakalopoulou, K Karantzalos, N Paragios, B Le Saux, ... IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017 | 85 | 2017 |
| Artificial intelligence in lung cancer: current applications and perspectives G Chassagnon, C De Margerie-Mellon, M Vakalopoulou, R Marini, ... Japanese journal of radiology 41 (3), 235-244, 2023 | 77 | 2023 |
| Benchmarking deep learning frameworks for the classification of very high resolution satellite multispectral data M Papadomanolaki, M Vakalopoulou, S Zagoruyko, K Karantzalos ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2016 | 74 | 2016 |
| Radiomics to predict outcomes and abscopal response of patients with cancer treated with immunotherapy combined with radiotherapy using a validated signature of CD8 cells R Sun, N Sundahl, M Hecht, F Putz, A Lancia, A Rouyar, M Milic, A Carré, ... Journal for Immunotherapy of Cancer 8 (2), 2020 | 73 | 2020 |
| U-ReSNet: Ultimate coupling of registration and segmentation with deep nets T Estienne, M Vakalopoulou, S Christodoulidis, E Battistela, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 72 | 2019 |
| Self-supervised nuclei segmentation in histopathological images using attention M Sahasrabudhe, S Christodoulidis, R Salgado, S Michiels, S Loi, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 65 | 2020 |
