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Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Amine Elforaici, M. E., Montagnon, E., Azzi, F., Trudel, D., Nguyen, B., Turcotte, S., Tang, A., & Kadoury, S. (2022, March). Semi-Supervised Tumor Response Grade Classification from Histology Images of Colorectal Liver Metastases [Paper]. 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI 2022), Kolkata, India (5 pages). External link
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). External link
Elforaici, M. E. A., Azzi, F., Trudel, D., Nguyen, B., Montagnon, E., Tang, A., Turcotte, S., & Kadoury, S. (2024, May). Cell-Level GNN-Based Prediction of Tumor Regression Grade in Colorectal Liver Metastases From Histopathology Images [Paper]. 21st IEEE International Symposium on Biomedical Imaging (ISBI 2024), Athens, Greece (5 pages). External link
Maaref, A., Romero, F. P., Montagnon, E., Cerny, M., Nguyen, B., Vandenbroucke, F., Soucy, G., Turcotte, S., Tang, A., & Kadoury, S. (2020). Predicting the Response to FOLFOX-Based Chemotherapy Regimen from Untreated Liver Metastases on Baseline CT: a Deep Neural Network Approach. Journal of Digital Imaging, 33(4), 937-945. External link
Vianna, P., Kulbay, M., Boustros, P., Calce, S.-I., Larocque-Rigney, C., Patry-Beaudoin, L., Luo, Y. H., Chaudary, M., Kadoury, S., Nguyen, B., Montagnon, E., Belilovsky, E., Wolf, G., Chassé, M., Tang, A., & Cloutier, G. (2023, September). Automated liver segmentation and steatosis grading using deep learning on B-mode ultrasound images [Paper]. IEEE International Ultrasonics Symposium (IUS 2023), Montreal, Qc, Canada (4 pages). External link
