Extracting the coronary artery tree in angiographic projections based on probability tracking

Using the tracking-based methods segmenting the coronary artery tree in X-Ray Angiogram (XRA), the traditional methods were subject to the blood vessels node and the local high curvature. To overcome the disadvantages, we presented a Multi-Features Measure (MFM) based Probability Tracking Model (PTM) to extract the blood vessel tree, and used a centerline operator to optimize the vessel skeleton-line. In the experiments, the proposed method on one hand avoids the problems of the traditional one; on the other hand the low time-consuming, the high robustness and the full automation are attained. Given an initial point in the interest vessel object, over 80% of the visible vessel branches in XRA image can be automatically delineated.