title: Topo-geometric filtration scheme for geometric active contours and level sets: application to cerebrovascular segmentation.
abstract: One of the main problems of the existing methods for the segmentation of cerebral vasculature is the appearance in the segmentation result of wrong topological artefacts such as the kissing vessels. In this paper, a new approach for the detection and correction of such errors is presented. The proposed technique combines robust topological information given by Persistent Homology with complementary geometrical information of the vascular tree. The method was evaluated on 20 images depicting cerebral arteries. Detection and correction success rates were 81.80% and 68.77%, respectively.
authors.forename: Helena
authors.initials: H
authors.lastname: Molina-Abril
authors.forename: Alejandro F
authors.initials: AF
authors.lastname: Frangi
mesh_terms: D000465:Algorithms; D002533:Cerebral Angiography / Q000379:methods*; D002536:Cerebral Arteries / 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; D013382:Subtraction Technique