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

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5242)

Abstract

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.

Keywords

Computational Fluid Dynamics Wall Shear Stress Abdominal Aortic Aneurysm Proper Orthogonal Decomposition Reconstruction Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Supplementary material

978-3-540-85990-1_94_MOESM1_ESM.zip (8.5 mb)
Electronic Supplementary Material (8,724 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  1. 1.Computer Vision Laboratory, Department of Electrical EngineeringETHZürichSwitzerland
  2. 2.Department of Mechanical EngineeringIndian Institute of Technology KanpurKanpurIndia

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