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1) C. Bang, W. T. Le, P. Nguyen, E. Filion, D. Soulieres, D. O鈥橲ullivan, A. Christopoulos, E. Bissada, T. Ayad, L. Guertin, A. Lalonde, D. Markel, S. Kadoury, H. Bahig, Dynamic prediction of head and neck cancer radiotherapy (HNC RT) toxicities using a 3D convolutional neural network (CNN) based on daily Cone-beam Computed Tomography (CBCT), International Journal of Radiation Oncology, Biology, Physics. 2024; 117(2):S55 dx.doi.org/10.1016/j.ijrobp.2023.06.346.
2) J. Duchaine, D. Markel, J Luc-Ley, D. B茅liveau-Nadeau, K. Zerouali, R. Doucet and H. Bouchard, Technical Note: Consistency of IAEA's TRS-483 and AAPM's extended TG-51 protocols for clinical reference dosimetry of the CyberKnife M6 machine, J. App. Clin. Med. Phys.. 2023; 24 (5) dx.doi.org/10.1002/acm2.13976
3) J. Duchaine, M. Wahl, D. Markel, H. Bouchard, A probabilistic approach for determining Monte Carlo beam source parameters: II. Impact of beam modeling uncertainties on dosimetric functions and treatment plans, Phys. Med. Bio. 2022; 67 (4) dx.doi.org/10.1088/1361-6560/ac4ei
4) J. Duchaine, D. Markel, H. Bouchard, A probabilistic approach for determining Monte Carlo beam source parameters: I. Modeling of a CyberKnife M6 unit, Phys. Med. Bio. 2022; 67 (4) dx.doi.org/10.1088/1361-6560/ac4ef7
5) J. Duchaine, D. Markel, H. Bouchard, Efficient dose-rate correction of silicon diode relative dose measurements, Med. Phys. 2022; 49(6):4056-4070. dx.doi.org/10.1002/mp.15628
6) G. Chartrand, R. Emiliani, S. A. Pawlowski, D. Markel, H. Bahig, A. Cengarle-Samak, S. Rajakesari, J. Lavoie, S. Ducharme, D. Roberge, Automated Detection of Brain Metastases on T1-Weighted MRI Using a Convolutional Neural Network: Impact of Volume Aware Loss and Sampling Strategy, J. Magn. Res. Im. 2022. dx.doi.org/10.1002/jmri.28272
7) D. Markel, I.R. Levesque, J. Larkin, P. Leger, I. El Naqa, A 4D biomechanical lung phantom for joint segmentation/registration evaluation, Phys. Med. Bio., 2016; 61(19):7012-7030. dx.doi.org/10.1088/0031-9155/61/19/7012