Automatic Bifurcation Detection in Coronary X-Ray Angiographies

Abstract

The detection of vascular bifurcation in X-ray images is important for several medical applications. They are used as landmarks for image registration, vessel segmentation and tracking. Although many bifurcation extraction methods have been proposed in recent years, very few work deals with coronary bifurcation in X-ray images. In this paper, we present a new bifurcation detector based on the multiscale Hessian analysis. It can be seen as a scale specific Histogram of Eigenvectors weighted by the vesselness measure. Pixels with three peaks in their immediate neighbourhood are considered as bifurcation candidates. Based on this detector, a novel bifurcationness measure is proposed. The method is tested on real coronary artery angiographies and shows better results compared to other bifurcation detectors.