In this paper we describe techniques to determine the skeleton of coronary arteries and to measure their medically significant geometric properties (such as boundaries and orientations) in cineangiograms. We use these geometric properties for segmentation, i.e., for separating the image of the arteries from the background. The purpose of this segmentation is to produce a structural description of the arterial tree for high-level processing. Our technique is completely automatic, efficient, and reliable. Our technique starts with the detection of skeleton points from a local ridge detector using density profiles of the arteries. Local orientations of skeleton points are obtained directly from the ridge detection or from local edge directions. Boundaries of the arteries are computed from the density profile along a straight line perpendicular to the skeleton. From this, a sequential and raster-scan tracking procedure is applied to obtain segments of the arteries from two scanning directions. The final segments are generated by merging all the segments.
Algorithms Cineangiography