Paper
21 March 2014 Blood flow quantification using optical flow methods in a body fitted coordinate system
Peter Maday, Richard Brosig, Jurgen Endres, Markus Kowarschik, Nassir Navab
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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.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter Maday, Richard Brosig, Jurgen Endres, Markus Kowarschik, and Nassir Navab "Blood flow quantification using optical flow methods in a body fitted coordinate system", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90340J (21 March 2014); https://doi.org/10.1117/12.2043408
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KEYWORDS
Image segmentation

Electroluminescent displays

Angiography

3D image processing

3D acquisition

3D metrology

Blood

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