title: CTA coronary labeling through efficient geodesics between trees using anatomy priors.
abstract: We present an efficient realization of recent work on unique geodesic paths between tree shapes for the application of matching coronary arteries to a standard model of coronary anatomy in order to label the coronary arteries. Automatically labeled coronary arteries would speed reporting for physicians. The efficiency of the approach and the quality of the results are enhanced using the relative position of detected cardiac structures. We explain how to efficiently compute the geodesic paths between tree shapes using Dijkstra's algorithm and we present a methodology to account for missing side branches during matching. For nearly all labels our approach shows promise compared with recent work and we results for 8 additional labels.
authors.forename: Mehmet A
authors.initials: MA
authors.lastname: Gülsün
authors.forename: Gareth
authors.initials: G
authors.lastname: Funka-Lea
authors.forename: Yefeng
authors.initials: Y
authors.lastname: Zheng
authors.forename: Matthias
authors.initials: M
authors.lastname: Eckert
mesh_terms: D059925:Anatomic Landmarks / Q000000981:diagnostic imaging*; D001185:Artificial Intelligence; D017023:Coronary Angiography / Q000379:methods*; D003331:Coronary Vessels / Q000000981:diagnostic imaging*; D004282:Documentation / Q000379:methods*; D006801:Humans; D008954:Models, Biological; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*