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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.
Benovoy, M., Jacobs, M., Cheriet, F., Dahdah, N., Arai, A. E., & Hsu, L.-Y. (2017). Robust Universal Nonrigid Motion Correction Framework for First-Pass Cardiac MR Perfusion Imaging. Journal of Magnetic Resonance Imaging, 46(4), 1060-1072. External link
Benovoy, M. (2016). Automatic Spatiotemporal Analysis of Cardiac Image Series [Ph.D. thesis, École Polytechnique de Montréal]. Available
Benovoy, M., Dionne, A., Cheriet, F., Maurice, R. L., & Dahdah, N. (2016). Correlation between automatic angio-based coronary artery stiffness assessment and visual oct pathology scoring. Journal of the American College of Cardiology, 67(13), 1672-1672. External link
Benovoy, M., Cheriet, F., Maurice, R. L., & Dahdah, N. (2015). Abstract 153: Automated Angiographic Assessment Of Coronary Artery Vasomotion In Kawasaki Disease Patients. Circulation, 131(suppl_2). External link
Benovoy, M., Jacobs, M., Cheriet, F., Dahdah, N., Arai, A. E., & Li-Yueh, H. (2015, April). Automatic nonrigid motion correction for quantitative first-pass cardiac MR perfusion imaging [Paper]. 12th IEEE International Symposium on Biomedical Imaging (ISBI 2015), New York, NY. External link
Gold, B. P., Mas-Herrero, E., Zeighami, Y., Benovoy, M., Dagher, A., & Zatorre, R. J. (2019). Musical reward prediction errors engage the nucleus accumbens and motivate learning. Proceedings of the National Academy of Sciences of the United States of America, 116(8), 3310-3315. External link
Hsu, L.-Y., Kellman, P., Gatehouse, P., Conn, H., Benovoy, M., Jacobs, M., & Arai, A. E. (2016, January). Correlations and validations of dual-bolus and dual-sequence quantification of first-pass myocardial perfusion CMR in humans and canines [Paper]. 19th annual SCMR Scientific Sessions, Los Angeles, Calif. (2 pages). Published in Journal of Cardiovascular Magnetic Resonance, 18(S1). Available
Hsu, L.-Y., Jacobs, M., Benovoy, M., Conn, H., & Arai, A. E. (2016, January). Fully automated pixel-wise myocardial blood flow quantification with first-pass perfusion CMR [Presentation]. In 19th annual SCMR Scientific Session, Los Angeles, CA, USA (2 pages). Published in Journal of Cardiovascular Magnetic Resonance, 18(S1). Available
Jacobs, M., Benovoy, M., Chang, L.-C., Arai, A. E., & Hsu, L.-Y. (2016). Evaluation of an automated method for arterial input function detection for first-pass myocardial perfusion cardiovascular magnetic resonance. Journal of Cardiovascular Magnetic Resonance, 18(1), 1-11. Available
Jacobs, M., Gorbachev, M., Benovoy, M., Chang, L.-C., Arai, A. E., & Hsu, L.-Y. (2015, April). Automated measurement of arterial input function in first-pass myocardial perfusion magnetic resonance images using independent component analysis [Paper]. IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015), New York, États-Unis. External link
