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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.
Alley, S. (2024). Standardization of Multi-Parametric Magnetic Resonance Imaging for the Characterization of Prostate Cancer [Ph.D. thesis, Polytechnique Montréal]. Restricted access
Alley, S., Jackson, E., Olivié, D., van der Heide, U. A., Ménard, C., & Kadoury, S. (2022). Effect of magnetic resonance imaging pre-processing on the performance of model-based prostate tumor probability mapping. Physics in Medicine & Biology, 67(24), 3796-3808. External link
Alley, S., Fedorov, A., Ménard, C., & Kadoury, S. (2020, February). Evaluation of intensity-based deformable registration of multi-parametric MRI for radiomics analysis of the prostate [Paper]. Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, Houston, Texas, USA (11 pages). External link
Alley, S., Gilbert, G., Wheeler-Kingshott, C. A. M. G., Samson, R. S., Grussu, F., Martin, A., Bannier, É., Callot, V., Smith, S. A., Xu, J., Dewey, B., Weber, K. A., Parrish, T., McLauren, D., Barker, G. J., Papinutto, N., Seif, M., Freund, P., Barry, R. L., ... Cohen-Adad, J. (2018, June). Consensus acquisition protocol for quantitative MRI of the cervical spinal cord at 3T [Poster]. Joint annual meeting ISMRM - ESMRMB, Paris, France. External link
Belliveau, C., Benhacene-Boudam, M.-K., Juneau, D., Plouznikoff, N., Olivié, D., Alley, S., Barkati, M., Delouya, G., Taussky, D., Lambert, C., Beauchemin, M.-C., & Ménard, C. (2025). F18-DCFPyL PSMA-PET/CT Versus MRI: Identifying the Prostate Cancer Region Most at Risk of Radiation Therapy Recurrence for Tumor Dose Escalation. Practical Radiation Oncology. External link
Cohen-Adad, J., Alonso Ortiz, E., Alley, S., Laganà, M. M., Baglio, F., Vannesjo, S. J., Karbasforoushan, H., Seif, M., Seifert, A. C., Xu, J., Kim, J.-W., Labounek, R., Vojtiek, L., Dostál, M., Valoek, J., Samson, R. S., Grussu, F., Battiston, M., Wheeler-Kingshott, C. A. M. G., ... Prados, F. (2022). Comparison of multicenter MRI protocols for visualizing the spinal cord gray matter. Magnetic Resonance in Medicine, 88(2), 849-859. External link
Lopera, D. O. G., Picot, F., Shams, R., Dallaire, F., Sheehy, G., Alley, S., Barkati, M., Delouya, G., Carrier, J.-F., Birlea, M., Trudel, D., Leblond, F., Ménard, C., & Kadoury, S. (2022). Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 2: in-vivo tumor-targeting using a classification model combining spectral and MRI-radiomics features. Journal of Biomedical Optics, 27(9), 095004 (16 pages). 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
