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Mezheritsky, T., Romaguera, L. V., Le, W. L., & Kadoury, S. (2022). Population-based 3D respiratory motion modelling from convolutional autoencoders for 2D ultrasound-guided radiotherapy. Medical Image Analysis, 75, 102260 (14 pages). Lien externe
Romaguera, L. V., Mezheritsky, T., Mansour, R., Tanguay, W., & Kadoury, S. (2021). Predictive online 3D target tracking with population-based generative networks for image-guided radiotherapy. International Journal of Computer Assisted Radiology and Surgery, 16(7), 1213-1225. Lien externe
Romaguera, L. V., Mezheritsky, T., Mansour, R., Carrier, J.-F., & Kadoury, S. (2021). Probabilistic 4D predictive model from in-room surrogates using conditional generative networks for image-guided radiotherapy. Medical Image Analysis, 74, 102250 (17 pages). Lien externe
Fong, D., Gregoire-Gelinas, P., Cheng, A. P., Mezheritsky, T., Lavertu, M., Sato, S., & Hoemann, C. D. (2017). Lysosomal rupture induced by structurally distinct chitosans either promotes a type 1 IFN response or activates the inflammasome in macrophages. Biomaterials, 129, 127-138. Disponible
Vazquez Romaguera, L., Mezheritsky, T., & Kadoury, S. (septembre 2021). Personalized Respiratory Motion Model Using Conditional Generative Networks for MR-Guided Radiotherapy [Communication écrite]. 24th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2021). Lien externe
Mezheritsky, T., Vazquez Romaguera, L., & Kadoury, S. (avril 2020). 3D Ultrasound Generation from Partial 2D Observations Using Fully Convolutional and Spatial Transformation Networks [Communication écrite]. 17th IEEE International Symposium on Biomedical Imaging (ISBI 2020), Iowa City, IA. Lien externe
Mezheritsky, T. (2021). Modélisation du mouvement tridimensionnel du foie à partir d'images échographiques 2D par auto-encodeurs convolutionnels [Mémoire de maîtrise, Polytechnique Montréal]. Disponible