Open Curvature Scale Space Matching for Coronary Artery Identification in X-Ray Angiographic Images

Identification of the coronary artery in sequence angiograms is an important issue in the analysis and treatment of coronary angiography data, due to the ambiguities in the coronary vessels resulting from cardiac motion and the differences in the projection angles in angiograms. In this paper, we propose a novel coronary artery identification method based on curvature scale space image matching. First, points on the centerline of each coronary artery branch are convolved with Gaussian kernel functions of different scales to obtain the corresponding curvature scale space (CSS) image during the curve evolution. Then, a CSS image matching method for open curves, which uses a combination of open feature vectors and closed feature vectors, is proposed. Finally, curve matching transitivity is used to solve the problem of the inability to recognize the coronary artery when the difference in the imaging angles is too large. The experimental results demonstrate that the proposed method can recognize every coronary artery in different views, even when the difference in the imaging angles is 29.8°.