title: Vessel tractography using an intensity based tensor model with branch detection.
abstract: In this paper, we present a tubular structure segmentation method that utilizes a second order tensor constructed from directional intensity measurements, which is inspired from diffusion tensor image (DTI) modeling. The constructed anisotropic tensor which is fit inside a vessel drives the segmentation analogously to a tractography approach in DTI. Our model is initialized at a single seed point and is capable of capturing whole vessel trees by an automatic branch detection algorithm developed in the same framework. The centerline of the vessel as well as its thickness is extracted. Performance results within the Rotterdam Coronary Artery Algorithm Evaluation framework are provided for comparison with existing techniques. 96.4% average overlap with ground truth delineated by experts is obtained in addition to other measures reported in the paper. Moreover, we demonstrate further quantitative results over synthetic vascular datasets, and we provide quantitative experiments for branch detection on patient computed tomography angiography (CTA) volumes, as well as qualitative evaluations on the same CTA datasets, from visual scores by a cardiologist expert.
authors.affiliation: Faculty of Engineering and Natural Sciences, Sabanci University, 34956 Istanbul, Turkey. suheylacetin@sabanciuniv.edu
authors.forename: Suheyla
authors.initials: S
authors.lastname: Cetin
authors.forename: Ali
authors.initials: A
authors.lastname: Demir
authors.forename: Anthony
authors.initials: A
authors.lastname: Yezzi
authors.forename: Muzaffer
authors.initials: M
authors.lastname: Degertekin
authors.forename: Gozde
authors.initials: G
authors.lastname: Unal
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D017023:Coronary Angiography / Q000379:methods*; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008953:Models, Anatomic; D010363:Pattern Recognition, Automated / Q000379:methods*; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*