Vessel centerline extraction from x-ray angiography (XRA) images is essential for vessel structure analysis in the diagnosis of coronary artery disease. However, complete and continuous centerline extraction remains a challenging task due to image noise, poor contrast, and complexity of vessel structure. Thus, an iterative multi-path search framework for automatic vessel centerline extraction is proposed. First, the seed points of the vessel structure are detected and sorted by confidence. With the ordered seed points, multibranch centerline is searched through multi-path propagation of wavefront and accumulated voting. Finally, the centerline is further extended piecewise by wavefront propagation on the basis of keypoint detection. The latter two steps are performed alternately to obtain the final centerline result. The proposed method is qualitatively and quantitatively evaluated on 1260 synthetic images and 50 clinical angiography images. The results demonstrate that our method achieves a high F_1 score of 87.8±2.7% for the angiography images. Compared with the other eight state-of-the-art methods, our method exhibits superior connectivity for coronary artery centerline extraction.
© 2021 Institute of Physics and Engineering in Medicine.