Title
Blood flow quantification using optical flow methods in a body fitted coordinate system
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-Christoffel(1) (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.
Year
DOI
Venue
2014
10.1117/12.2043408
Proceedings of SPIE
Keywords
Field
DocType
optical flow
Coordinate system,Boundary value problem,Computer vision,Finite difference,Flow (psychology),Ground truth,Inter frame,Artificial intelligence,Optical flow,Volumetric flow rate,Physics
Conference
Volume
ISSN
Citations 
9034
0277-786X
0
PageRank 
References 
Authors
0.34
5
5
Name
Order
Citations
PageRank
Peter Maday1182.18
richard brosig200.34
jurgen endres300.34
Markus Kowarschik422242.67
Nassir Navab56594578.60