  We present a method to extract coronary vessels from fluoroscopic x-ray
sequences. Given the vessel structure for the source frame, vessel
correspondence candidates in the subsequent frame are generated by a novel
hierarchical search scheme to overcome the aperture problem. Optimal
correspondences are determined within a Markov random field optimization
framework. Post-processing is performed to extract vessel branches newly
visible due to the inflow of contrast agent. Quantitative and qualitative
evaluation conducted on a dataset of 18 sequences demonstrates the
effectiveness of the proposed method.
