title: Detecting tubular structures via direct vector field singularity characterization.
abstract: The initial step of vessel segmentation in 3D is the detection of vessel centerlines. The proposed methods in literature are either dependent on vessel radius and/or have low response at vessel bifurcations. In this paper we propose a 3D tubular structure detection method that removes these two drawbacks. The proposed method exploits the observations on the eigenvalues of the Hessian matrix as is done in literature, yet it employs a direct 3D vector field singularity characterization. The Gradient Vector Flow vector field is used and the eigenvalues of its Jacobian are exploited in computing a parameter free vesselness map. Results on phantom and real patient data exhibit robustness to scale, high response at vessel bifurcations, and good noise/non-vessel structure suppression.
authors.affiliation: Department of Electrical and Electronics Engineering, Boğaziçi University, 34342, İstanbul, Turkey.
authors.forename: Aytekin D
authors.initials: AD
authors.lastname: Cabuk
authors.forename: Erdenay
authors.initials: E
authors.lastname: Alpay
authors.forename: Burak
authors.initials: B
authors.lastname: Acar
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*