Martin Vallières, PhD
Martin Vallières, PhD
Assistant Professor, Department of Computer Science, University of Sherbrooke
Verified email at - Homepage
Cited by
Cited by
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
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
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
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
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
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
Deep learning in head & neck cancer outcome prediction
A Diamant, A Chatterjee, M Vallières, G Shenouda, J Seuntjens
Scientific reports 9 (1), 2764, 2019
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
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
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, 864-877, 2019
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
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
Image biomarker standardisation initiative-feature definitions
A Zwanenburg, S Leger, M Vallières, S Löck
arXiv preprint arXiv:1612.07003 10, 2016
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, 299-307, 2019
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
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
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
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
Two-dimensional nanoscale structural and functional imaging in individual collagen type I fibrils
C Harnagea, M Vallières, CP Pfeffer, D Wu, BR Olsen, A Pignolet, ...
Biophysical journal 98 (12), 3070-3077, 2010
Automatic segmentation of head and neck tumors and nodal metastases in PET-CT scans
V Andrearczyk, V Oreiller, M Vallières, J Castelli, H Elhalawani, M Jreige, ...
Medical imaging with deep learning, 33-43, 2020
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