| The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping A Zwanenburg, M Vallières, MA Abdalah, HJWL Aerts, V Andrearczyk, ... Radiology 295 (2), 328-338, 2020 | 4238 | 2020 |
| A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities M Vallières, CR Freeman, SR Skamene, I El Naqa Physics in Medicine & Biology 60 (14), 5471, 2015 | 1019 | 2015 |
| Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer M Vallières, E Kay-Rivest, LJ Perrin, X Liem, C Furstoss, HJWL Aerts, ... Scientific Reports 7 (10117), 2017 | 655 | 2017 |
| Machine and deep learning methods for radiomics M Avanzo, L Wei, J Stancanello, M Vallieres, A Rao, O Morin, ... Medical physics 47 (5), e185-e202, 2020 | 636 | 2020 |
| 18F-FDG PET uptake characterization through texture analysis: investigating the complementary nature of heterogeneity and functional tumor volume in a multi–cancer site patient … M Hatt, M Majdoub, M Vallières, F Tixier, CC Le Rest, D Groheux, ... Journal of nuclear medicine 56 (1), 38-44, 2015 | 518 | 2015 |
| Federated learning enables big data for rare cancer boundary detection S Pati, U Baid, B Edwards, M Sheller, SH Wang, GA Reina, P Foley, ... Nature communications 13 (1), 7346, 2022 | 402 | 2022 |
| MRI features predict survival and molecular markers in diffuse lower-grade gliomas H Zhou, M Vallières, HX Bai, C Su, H Tang, D Oldridge, Z Zhang, B Xiao, ... Neuro-oncology 19 (6), 862-870, 2017 | 401 | 2017 |
| Head and neck tumor segmentation in PET/CT: the HECKTOR challenge V Oreiller, V Andrearczyk, M Jreige, S Boughdad, H Elhalawani, J Castelli, ... Medical image analysis 77, 102336, 2022 | 267 | 2022 |
| Deep learning in head & neck cancer outcome prediction A Diamant, A Chatterjee, M Vallières, G Shenouda, J Seuntjens Scientific reports 9 (1), 2764, 2019 | 257 | 2019 |
| METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII B Kocak, T Akinci D’Antonoli, N Mercaldo, A Alberich-Bayarri, B Baessler, ... Insights into imaging 15 (1), 8, 2024 | 230 | 2024 |
| Responsible radiomics research for faster clinical translation M Vallières, A Zwanenburg, B Badic, CC Le Rest, D Visvikis, M Hatt Journal of Nuclear Medicine 59 (2), 189-193, 2018 | 213 | 2018 |
| External validation of a combined PET and MRI radiomics model for prediction of recurrence in cervical cancer patients treated with chemoradiotherapy F Lucia, D Visvikis, M Vallières, MC Desseroit, O Miranda, P Robin, ... European journal of nuclear medicine and molecular imaging 46 (4), 864-877, 2019 | 205 | 2019 |
| Overview of the HECKTOR challenge at MICCAI 2021: automatic head and neck tumor segmentation and outcome prediction in PET/CT images V Andrearczyk, V Oreiller, S Boughdad, CCL Rest, H Elhalawani, ... 3D head and neck tumor segmentation in PET/CT challenge, 1-37, 2021 | 201 | 2021 |
| The image biomarker standardization initiative: standardized convolutional filters for reproducible radiomics and enhanced clinical insights P Whybra, A Zwanenburg, V Andrearczyk, R Schaer, AP Apte, A Ayotte, ... Radiology 310 (2), e231319, 2024 | 180 | 2024 |
| Deep learning to distinguish benign from malignant renal lesions based on routine MR imaging IL Xi, Y Zhao, R Wang, M Chang, S Purkayastha, K Chang, RY Huang, ... Clinical Cancer Research 26 (8), 1944-1952, 2020 | 165 | 2020 |
| Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low-and high-grade gliomas H Zhou, K Chang, HX Bai, B Xiao, C Su, WL Bi, PJ Zhang, JT Senders, ... Journal of neuro-oncology 142 (2), 299-307, 2019 | 150 | 2019 |
| Image biomarker standardisation initiative-feature definitions A Zwanenburg, S Leger, M Vallières, S Löck arXiv preprint arXiv:1612.07003 10, 2016 | 134 | 2016 |
| Integrated models incorporating radiologic and radiomic features predict meningioma grade, local failure, and overall survival O Morin, WC Chen, F Nassiri, M Susko, ST Magill, HN Vasudevan, A Wu, ... Neuro-oncology advances 1 (1), vdz011, 2019 | 120 | 2019 |
| A deep look into the future of quantitative imaging in oncology: a statement of working principles and proposal for change O Morin, M Vallières, A Jochems, HC Woodruff, G Valdes, SE Braunstein, ... International Journal of Radiation Oncology* Biology* Physics 102 (4), 1074-1082, 2018 | 118 | 2018 |
| Overview of the HECKTOR challenge at MICCAI 2020: automatic head and neck tumor segmentation in PET/CT V Andrearczyk, V Oreiller, M Jreige, M Vallières, J Castelli, H Elhalawani, ... 3D Head and Neck Tumor Segmentation in PET/CT Challenge, 1-21, 2021 | 115 | 2021 |
Issam El Naqa, PhD, FAAPM, FIEEE, F...Chair of Machine Learning, H. Lee Moffitt Cancer CenterVerified email at moffitt.org
