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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., Drotár, P., Vazquez Romaguera, L., & 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., Vazquez Romaguera, L., Huët, 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., Vazquez Romaguera, L., Huët, 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., Vazquez Romaguera, L., 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
Mezheritsky, T., Vazquez Romaguera, L., & Kadoury, S. (2020, April). 3D Ultrasound Generation from Partial 2D Observations Using Fully Convolutional and Spatial Transformation Networks [Paper]. 17th IEEE International Symposium on Biomedical Imaging (ISBI 2020), Iowa City, IA. External link
Mansour, R., Thibodeau Antonacci, A., Bilodeau, L., Vazquez Romaguera, L., Cerny, M., Huët, C., Gilbert, G., Tang, A., & Kadoury, S. (2020). Impact of temporal resolution and motion correction for dynamic contrast-enhanced MRI of the liver using an accelerated golden-angle radial sequence. Physics in Medicine and Biology, 65(8), 16 pages. External link
Ouraou, E., Vazquez Romaguera, L., 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, T. V., Vazquez Romaguera, L., Piñol, D. C., & Seisdedos, C. R. V. (2021). Pupil Center Detection Approaches: A Comparative Analysis. Computacion Y Sistemas, 25(1), 67-81. External link
Thibeault, S., Vazquez Romaguera, L., & 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
Vazquez Romaguera, L., 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
Vazquez Romaguera, L. (2021). Image-Based Analysis and Modelling of Respiratory Motion Using Deep Learning Techniques [Ph.D. thesis, Polytechnique Montréal]. Available
Vazquez Romaguera, L., Mezheritsky, T., & Kadoury, S. (2021, September). Personalized Respiratory Motion Model Using Conditional Generative Networks for MR-Guided Radiotherapy [Paper]. 24th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2021). External link
Vazquez Romaguera, L., 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. External link
Vazquez Romaguera, L., 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
Vazquez Romaguera, L., Plantefève, R., Romero, F. P., Hébert, F., Carrier, J.-F., & Kadoury, S. (2020). Prediction of in-plane organ deformation during free-breathing radiotherapy via discriminative spatial transformer networks. Medical Image Analysis, 64, 14 pages. External link
Vazquez Romaguera, L., Plantefève, R., & Kadoury, S. (2019, February). Quantitative analysis of 4D MR volume reconstruction methods from dynamic slice acquisitions [Paper]. SPIE Medical Imaging 2019 : Image-Guided Procedures, Robotic Interventions, and Modeling (MI2019), San Diego, California, United States (6 pages). External link
