Blood Flow Estimation by Means of Intraoperative Rotational Angiographic System

We present an algorithm for estimating the blood flow in angiographic image data. In corresponding projective digital subtraction X-ray angiography (2D-DSA) data sets we analyze the correlation between Concentration Time Curves (CTC) of pixels along the vessel centerline. The appropriate spatial information is recovered by applying a 2D-3D registration re-projecting the centerline pixels to the reconstructed 3D X-ray rotation angiography (3D-RA) data of the same object. Ambiguities caused by occluding vessels are resolved by a graph-based approach. Finally, we end up in a framework for the estimation of a real spatial blood flow. This measure is used as boundary condition for blood flow CFD simulations. The algorithm has been tested on phantom data. First plausibility tests of this re-projection method on patient data indicate its ability to also properly function on these data.