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Proceedings Paper

Blood flow quantification using optical flow methods in a body fitted coordinate system
Author(s): Peter Maday; Richard Brosig; Jurgen Endres; Markus Kowarschik; Nassir Navab
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Paper Abstract

In this paper a blood flow quantification method that is based on a physically motivated dense 2D flow estimation algorithm is outlined. It yields accurate time varying volumetric flow rate measurements based on digital subtraction angiography (DSA) image sequences, with robustness to significant inter-frame displacements. Time varying volumetric flow rates are estimated for individual non-branching vascular segments based on the estimated 2D flow fields and a 3D vessel segmentation from a 3D Rotational Angiography (3DRA) acquisition. The novelty of the approach lies in the use of a vessel aligned coordinate system for the problem formulation. The coordinate functions are generated using the Schwarz-Christoffel1(SC) map that yields a solution with coordinate lines aligned with the vessel boundaries. The use of vessel aligned coordinates enables the easy and accurate handling of boundary conditions in the irregular domain of a vessel lumen while only requiring slight modifications to the used finite difference approach. Unlike traditional coarse to fine methods we use an anisotropic scaling strategy that enables the estimation of flows with larger inter frame displacements. The evaluation of our method is based on highly realistic synthetic DSA datasets for a number of cases. Ground truth volumetric flow rate values are compared against the measurements and a high degree of fidelity is observed. Performance measures are obtained with varying flow velocities and acquisition rates.

Paper Details

Date Published: 21 March 2014
PDF: 6 pages
Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90340J (21 March 2014); doi: 10.1117/12.2043408
Show Author Affiliations
Peter Maday, Technische Univ. München (Germany)
Richard Brosig, Technische Univ. München (Germany)
Jurgen Endres, Friedrich-Alexander-Univ. Erlangen-Nürnberg (Germany)
Markus Kowarschik, Siemens AG (Germany)
Nassir Navab, Technische Univ. München (Germany)

Published in SPIE Proceedings Vol. 9034:
Medical Imaging 2014: Image Processing
Sebastien Ourselin; Martin A. Styner, Editor(s)

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