Obtaining high quality patient-specific flow velocity information is not an easy task. Available clinical data are usually poorly resolved and contain a significant amount of noise. We propose a novel approach to integrate computational fluid dynamics with measurement data to overcome this difficulty. By performing a proper orthogonal decomposition of simulated blood flow patterns for a given vascular location with various anatomical configurations it is possible to obtain a basis model for flow reconstruction. This is used to interpolate imaging data intelligently without having to perform a full flow simulation for each individual patient. This work focuses on assessing the feasibility of such a method. © 2008 Springer Berlin Heidelberg.
CITATION STYLE
McGregor, R., Szczerba, D., Von Siebenthal, M., Muralidhar, K., & Székely, G. (2008). Exploring the use of proper orthogonal decomposition for enhancing blood flow images via computational fluid dynamics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5242 LNCS, pp. 782–789). Springer Verlag. https://doi.org/10.1007/978-3-540-85990-1_94
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