Exploring the use of proper orthogonal decomposition for enhancing blood flow images via computational fluid dynamics.
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.
McGregor
R H P
RH
Computer Vision Laboratory, Department of Electrical Engineering, ETH, 8092 Zürich, Switzerland.
Szczerba
D
D
von Siebenthal
M
M
Muralidhar
K
K
Székely
G
G
D001783:Blood Flow Velocity; D001921:Brain / Q000098:blood supply* / Q000502:physiology*; D002560:Cerebrovascular Circulation / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008955:Models, Cardiovascular