Validation study of two artificial intelligence–based preplanning methods for transcatheter aortic valve replacement procedures

Denis Corbin, Marcel Santaló-Corcoy, Olivier Tastet, Patricia Lopes, Janelle Schrot, Thomas Modine, Anita Asgar, Frédéric Lesage and Walid Ben Ali

Article (2024)

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Uncontrolled Keywords

• automatic preoperative planning
• deep neural networks
• transcatheter aortic valve replacement

Department:	Department of Electrical Engineering
Funders:	Fond de Recherche du Québec - Santé - Personnel Hautement Qualifié
PolyPublie URL:	https://publications.polymtl.ca/58193/
Journal Title:	Journal of the Society for Cardiovascular Angiography & Interventions (vol. 3, no. 3)
Publisher:	Elsevier
DOI:	10.1016/j.jscai.2023.101289
Official URL:	https://doi.org/10.1016/j.jscai.2023.101289
Date Deposited:	21 May 2024 10:48
Last Modified:	08 Jan 2026 15:15

Cite in APA 7:	Corbin, D., Santaló-Corcoy, M., Tastet, O., Lopes, P., Schrot, J., Modine, T., Asgar, A., Lesage, F., & Ali, W. B. (2024). Validation study of two artificial intelligence–based preplanning methods for transcatheter aortic valve replacement procedures. Journal of the Society for Cardiovascular Angiography & Interventions, 3(3), 101289 (2 pages). https://doi.org/10.1016/j.jscai.2023.101289
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