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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.
Gazda, M., Drotar, P., Romaguera, L. V., & Kadoury, S. (2023, April). End-To-End Deformable Attention Graph Neural Network for Single-View Liver Mesh Reconstruction [Paper]. 20th IEEE International Symposium on Biomedical Imaging (ISBI 2023), Cartagena, Colombia (5 pages). External link
Mansour, R., Romaguera, L. V., Huet, C., Bentridi, A., Vu, K.-N., Billiard, J.-S., Gilbert, G., Tang, A., & Kadoury, S. (2022). Abdominal motion tracking with free-breathing XD-GRASP acquisitions using spatio-temporal geodesic trajectories. Medical and Biological Engineering and Computing, 60(2), 583-598. External link
Mansour, R., Romaguera, L. V., Huet, C., Bentridi, A., Vu, K.N., Billiard, J. S., Gilbert, G., Tang, A., & Kadoury, S. (2022). Correction to: Abdominal motion tracking with freebreathing XDGRASP acquisitions using spatiotemporal geodesic trajectories. Medical and Biological Engineering and Computing, 60(4), 1223-1223. External link
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). External link
Ouraou, E., Romaguera, L. V., Tonneau, M., Bahig, H., & Kadoury, S. (2023, February). Prediction of free-breathing 4DCT lung deformation using probabilistic motion auto-encoders [Paper]. Medical Imaging 2023: Image-Guided Procedures, Robotic Interventions, and Modeling, San Diego, CA, USA (7 pages). External link
Romaguera, L. V., Alley, S., Carrier, J.-F., & Kadoury, S. (2023). Conditional-based Transformer network with learnable queries for 4D deformation forecasting and tracking. IEEE Transactions on Medical Imaging, 42(6), 1603-1618. External link
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). External link
Thibeault, S., Romaguera, L. V., & Kadoury, S. (2024, October). Conditional 4D Motion Diffusion Models with Masked Observations to Forecast Deformations [Paper]. 27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2024), Marrakesh, Morocco. External link
