Exploring the Use of Proper Orthogonal Decomposition for Enhancing Blood Flow Images Via Computational Fluid Dynamics

Robert McGregor, Dominik Szczerba, Martin von Siebenthal, Krishnamurthy Muralidhar, and Gábor Székely, Lecture Notes in Computer Science: Medical Image Computing and Computer-Assisted Intervention 5242/2008, pp. 782–789, October 2008

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.

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