3D coronary modeling extracts the centerlines and width of the coronary arteries from a rotational sequence
of angiographies. This process heavily relies on a preliminary filtering of the 2D angiograms that enhances the
vessels. We propose an improved vessel enhancement method specifically designed for this application. It keeps
the advantages of Hessian-based extraction methods (speed, robustness, multiscale) while bypassing its more
important limitations: the blurring of bifurcations, and the incomplete filling of very large vessels.
The major contributions of this paper are twofold. First, the classical centered kernel used in Hessian-based
methods is substituted with an elongated off-centered kernel. The new filter detects the different orientations
involved at a bifurcation: it can answer properly to 'half vessels' beginning at the considered pixel (as opposed
to the centered classical filter). The proposed "semi-oriented ridge" filter is also more robust to noise, and it
stays multi-scale and quickly computable.
Second, an original bifurcation detection and enhancement method is presented, based on the following heuristics:
"bifurcations have three vessels (at least) in their immediate neighborhood". More precisely, the semi-oriented
ridges answers in each tested orientation θ∈]-π,π] are stored in a circular histogram. The proposed bifurcation
energy is the height of the third peak in this histogram: it will have a significant value at bifurcations only.
The performance of the complete framework is demonstrated both on the produced vessel maps and on the final