title: Automatic generation of 3D coronary artery centerlines using rotational X-ray angiography.
abstract: A fully automated 3D centerline modeling algorithm for coronary arteries is presented. It utilizes a subset of standard rotational X-ray angiography projections that correspond to one single cardiac phase. The algorithm is based on a fast marching approach, which selects voxels in 3D space that belong to the vascular structure and introduces a hierarchical order. The local 3D propagation speed is determined by a combination of corresponding 2D projections filtered with a vessel enhancing kernel. The best achievable accuracy of the algorithm is evaluated on simulated projections of a virtual heart phantom, showing that it is capable of extracting coronary centerlines with an accuracy that is mainly limited by projection and volume quantization (0.25 mm). The algorithm is reasonably insensitive to residual motion, which means that it is able to cope with inconsistencies within the projection data set caused by limited gating accuracy and respiration. Its accuracy on clinical data is evaluated based on expert ratings of extracted models of 17 consecutive clinical cases (10 LCA, 7 RCA). A success rate of 93.5% (i.e. with no or slight deviations) is achieved compared to 58.8% success rate of semi-automatically extracted models.
authors.affiliation: Philips Technologie GmbH Forschungslaboratorien, Röntgenstrasse 24-26, 22335 Hamburg, Germany. uwe.jandt@tu-harburg.de
authors.forename: Uwe
authors.initials: U
authors.lastname: Jandt
authors.forename: Dirk
authors.initials: D
authors.lastname: Schäfer
authors.forename: Michael
authors.initials: M
authors.lastname: Grass
authors.forename: Volker
authors.initials: V
authors.lastname: Rasche
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D017023:Coronary Angiography / Q000379:methods*; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity