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Gotra, A., Sivakumaran, L., Chartrand, G., Vu, K.-N., Vandenbroucke-Menu, F., Kauffmann, C., Kadoury, S., Gallix, B., de Guise, J. A., & Tang, A. (2017). Liver segmentation: indications, techniques and future directions. Insights into Imaging, 8(4), 377-392. Disponible
Montagnon, E., Cerny, M., Cadrin-Chênevert, A., Hamilton, V., Derennes, T., Ilinca, A., Vandenbroucke-Menu, F., Turcotte, S., Kadoury, S., & Tang, A. (2020). Deep learning workflow in radiology: a primer. Insights into Imaging, 11(22), 15 pages. Lien externe
Romero, F. P., Diler, A., Bisson-Gregoire, G., Turcotte, S., Lapointe, R., Vandenbroucke-Menu, F., Tang, A., & Kadoury, S. (avril 2019). End-to-end discriminative deep network for liver lesion classification [Communication écrite]. 16th IEEE International Symposium on Biomedical Imaging (ISBI 2019), Venice, Italy. Lien externe
Vorontsov, E., Cerny, M., Régnier, P., Di Jorio, L., Pal, C. J., Lapointe, R., Vandenbroucke-Menu, F., Turcotte, S., Kadoury, S., & Tang, A. (2019). Deep learning for automated segmentation of liver lesions at cCT in patients with colorectal cancer liver metastases. Radiology: Artificial Intelligence, 1(2), 180014. Lien externe
