| 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 | 1770 | 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 | 909 | 2018 |
| LIFEx: a freeware for radiomic feature calculation in multimodality imaging to accelerate advances in the characterization of tumor heterogeneity C Nioche, F Orlhac, S Boughdad, S Reuzé, J Goya-Outi, C Robert, ... Cancer research 78 (16), 4786-4789, 2018 | 826 | 2018 |
| Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology EJ Limkin, R Sun, L Dercle, EI Zacharaki, C Robert, S Reuzé, ... Annals of Oncology 28 (6), 1191-1206, 2017 | 618 | 2017 |
| A review of the use and potential of the GATE Monte Carlo simulation code for radiation therapy and dosimetry applications D Sarrut, M Bardiès, N Boussion, N Freud, S Jan, JM Létang, G Loudos, ... Medical physics 41 (6Part1), 064301, 2014 | 520 | 2014 |
| 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 | 180 | 2020 |
| Prediction of cervical cancer recurrence using textural features extracted from 18F-FDG PET images acquired with different scanners S Reuzé, F Orlhac, C Chargari, C Nioche, E Limkin, F Riet, A Escande, ... Oncotarget 8 (26), 43169, 2017 | 142 | 2017 |
| Predictive and prognostic value of CT based radiomics signature in locally advanced head and neck cancers patients treated with concurrent chemoradiotherapy or bioradiotherapy … D Ou, P Blanchard, S Rosellini, A Levy, F Nguyen, RTH Leijenaar, ... Oral oncology 71, 150-155, 2017 | 104 | 2017 |
| Radiomics in nuclear medicine applied to radiation therapy: methods, pitfalls, and challenges S Reuzé, A Schernberg, F Orlhac, R Sun, C Chargari, L Dercle, E Deutsch, ... International Journal of Radiation Oncology* Biology* Physics 102 (4), 1117-1142, 2018 | 102 | 2018 |
| The complexity of tumor shape, spiculatedness, correlates with tumor radiomic shape features EJ Limkin, S Reuzé, A Carré, R Sun, A Schernberg, A Alexis, E Deutsch, ... Scientific reports 9 (1), 4329, 2019 | 91 | 2019 |
| Brain tumor segmentation with self-ensembled, deeply-supervised 3D U-net neural networks: a BraTS 2020 challenge solution T Henry, A Carré, M Lerousseau, T Estienne, C Robert, N Paragios, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2021 | 86 | 2021 |
| Monte Carlo calculations of positron emitter yields in proton radiotherapy E Seravalli, C Robert, J Bauer, F Stichelbaut, C Kurz, J Smeets, CVN Ty, ... Physics in Medicine & Biology 57 (6), 1659, 2012 | 85 | 2012 |
| 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 | 61 | 2019 |
| 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 | 56 | 2020 |
| Deep learning-based concurrent brain registration and tumor segmentation T Estienne, M Lerousseau, M Vakalopoulou, E Alvarez Andres, ... Frontiers in computational neuroscience 14, 17, 2020 | 50 | 2020 |
| Context aware 3D CNNs for brain tumor segmentation S Chandra, M Vakalopoulou, L Fidon, E Battistella, T Estienne, R Sun, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019 | 43 | 2019 |
| A freeware for tumor heterogeneity characterization in PET, SPECT, CT, MRI and US to accelerate advances in radiomics C Nioche, F Orlhac, S Boughdad, S Reuze, M Soussan, C Robert, ... Journal of Nuclear Medicine 58 (supplement 1), 1316-1316, 2017 | 43 | 2017 |
| Reinventing radiation therapy with machine learning and imaging bio-markers (radiomics): State-of-the-art, challenges and perspectives L Dercle, T Henry, A Carré, N Paragios, E Deutsch, C Robert Methods 188, 44-60, 2021 | 41 | 2021 |
| A score combining baseline neutrophilia and primary tumor SUVpeak measured from FDG PET is associated with outcome in locally advanced cervical cancer A Schernberg, S Reuze, F Orlhac, I Buvat, L Dercle, R Sun, E Limkin, ... European journal of nuclear medicine and molecular imaging 45, 187-195, 2018 | 35 | 2018 |
| Simulation-based evaluation and optimization of a new CdZnTe gamma-camera architecture (HiSens) C Robert, G Montémont, V Rebuffel, I Buvat, L Guérin, L Verger Physics in Medicine & Biology 55 (9), 2709, 2010 | 33 | 2010 |
Sylvain ReuzéGE HealthCareAdresse e-mail validée de ge.com
