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In this paper, we propose a fully automatic algorithm named adaptive geometrical vessel tracking (AGVT) for coronary artery identification in X-ray angiograms. Initially, the ridge enhancement (RE) image is obtained utilizing multiscale Hessian information. Then, automatic initialization procedures including seed points detection, and initial directions determination are performed on the RE image. The extracted ridge points can be adjusted to the geometrical centerline points adaptively through diameter estimation. Bifurcations are identified by discriminating connecting relationship of the tracked ridge points. Finally, all the tracked centerlines are merged and smoothed by classifying the connecting components on the vascular structures. Synthetic angiographic images and clinical angiograms are used to evaluate the performance of the proposed algorithm. The proposed algorithm is compared with other two vascular tracking techniques in terms of the efficiency and accuracy, which demonstrate successful applications of the proposed segmentation and extraction scheme in vasculature identification.<\/jats:p>","DOI":"10.1155\/2013\/796342","type":"journal-article","created":{"date-parts":[[2013,10,22]],"date-time":"2013-10-22T21:44:55Z","timestamp":1382478295000},"page":"1-11","source":"Crossref","is-referenced-by-count":8,"title":["Automatic Vasculature Identification in Coronary Angiograms by Adaptive Geometrical Tracking"],"prefix":"10.1155","volume":"2013","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3959-9797","authenticated-orcid":true,"given":"Ruoxiu","family":"Xiao","sequence":"first","affiliation":[{"name":"Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of China, School of Optics and Electronics, Beijing Institute of Technology, Beijing 10081, 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