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Documents dont l'auteur est "Le, William Trung"

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Nombre de documents: 10

Elforaici, M. E. A., Montagnon, E., Romero, F. P., Le, W. T., Azzi, F., Trudel, D., Nguyen, B., Turcotte, S., Tang, A., & Kadoury, S. (2025). Semi-supervised ViT knowledge distillation network with style transfer normalization for colorectal liver metastases survival prediction. Medical Image Analysis, 99, 103346 (16 pages). Lien externe

de Boisredon d’Assier, M. A., Portafaix, A., Vorontsov, E., Le, W. T., & Kadoury, S. (2024). Image-level supervision and self-training for transformer-based cross-modality tumor segmentation. Medical Image Analysis, 97, 103287 (16 pages). Lien externe

Bang, C., Le, W. T., Nguyen-Tan, P. F., Soulières, D., O'Sullivan, B., Christopoulos, A., Bissada, É., Ayad, T., Guertin, L., Lalonde, A., Markel, D., Kadoury, S., & Bahig, H. (octobre 2023). Dynamic Prediction of Toxicities in Head and Neck Cancer Radiotherapy by 3D Convolutional Neural Network Using Daily Cone-Beam CTs [Résumé]. 65th Annual Meeting of the American Society for Radiation Oncology (ASTRO 2023), San Diego, CA, USA (1 page). Publié dans International Journal of Radiation Oncology Biology Physics, 117(2). Lien externe

Bang, C., Le, W. T., Nguyen-Tan, P. F., Filion, É., Soulières, D., O'Sullivan, B., Christpoulos, A., Bissada, É., Ayad, T., Guertin, L., Lalonde, A., Markel, D., Kadoury, S., & Bahig, H. (septembre 2023). Dynamic prediction of toxicities in head and neck cancer radiotherapy by 3D convolutional neural network using daily cone-beam CTS [Résumé]. CARO-COMP Joint Scientific Meeting (CARO-COMP 2023), Montréal, Québec, Canada (1 page). Publié dans Radiotherapy and Oncology, 186(Suppl.1). Lien externe

Le, W. T., Bang, C., Cordelle, P., Markel, D., Nguyen-Tan, P. F., Bahig, H., & Kadoury, S. (avril 2023). Prediction of Head and Neck Radiotherapy Toxicity Using a Deformable 3D CNN on Longitudinal Daily CBCT Acquisitions [Communication écrite]. 20th IEEE International Symposium on Biomedical Imaging (ISBI 2023), Cartagena, Colombia (5 pages). Lien externe

Le, W. T., Vorontsov, E., Romero, F. P., Seddik, L., Elsharief, M. M., Nguyen-Tan, P. F., Roberge, D., Bahig, H., & Kadoury, S. (2022). Cross-institutional outcome prediction for head and neck cancer patients using self-attention neural networks. Scientific Reports, 12(1), 17 pages. Lien externe

Grajales, D., Kadoury, S., Shams, R., Barkati, M., Delouya, G., Béliveau-Nadeau, D., Nicolas, B., Le, W. T., Benhacene-Boudam, M.-K., Juneau, D., DaSilva, J. N., Carrier, J.-F., Hautvast, G., & Ménard, C. (2022). Performance of an integrated multimodality image guidance and dose-planning system supporting tumor-targeted HDR brachytherapy for prostate cancer. Radiotherapy and Oncology, 166, 154-161. Lien externe

Touati, R., Le, W. T., & Kadoury, S. (2021). A feature invariant generative adversarial network for head and neck MRI/CT image synthesis. Physics in Medicine and Biology, 66(9), 18 pages. Lien externe

Maleki, F., Le, W. T., Sananmuang, T., Kadoury, S., & Forghani, R. (2020). Machine Learning Applications for Head and Neck Imaging. Neuroimaging Clinics of North America, 30(4), 517-529. Lien externe

Le, W. T., Maleki, F., Romero, F. P., Forghani, R., & Kadoury, S. (2020). Overview of Machine Learning: Part 2 Deep Learning for Medical Image Analysis. Neuroimaging Clinics of North America, 30(4), 417-431. Lien externe

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