title: Automated segmentation and characterization of choroidal vessels in high-penetration optical coherence tomography.
abstract: An automated choroidal vessel segmentation and quantification method for high-penetration optical coherence tomography (OCT) was developed for advanced visualization and evaluation of the choroidal vasculature. This method uses scattering OCT volumes for the segmentation of choroidal vessels by using a multi-scale adaptive threshold. The segmented choroidal vessels are then processed by multi-scale morphological analysis to quantify the vessel diameters. The three-dimensional structure and the diameter distribution of the choroidal vasculature were then obtained. The usefulness of the method was then evaluated by analyzing the OCT volumes of normal subjects.
authors.affiliation: Computational Optics Group, University of Tsukuba, Tsukuba, Ibaraki, Japan.
authors.forename: Lian
authors.initials: L
authors.lastname: Duan
authors.forename: Young-Joo
authors.initials: YJ
authors.lastname: Hong
authors.forename: Yoshiaki
authors.initials: Y
authors.lastname: Yasuno
mesh_terms: D000465:Algorithms; D000792:Angiography; D001331:Automation; D002829:Choroid / Q000033:anatomy & histology* / Q000098:blood supply* / Q000000981:diagnostic imaging; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007208:Indocyanine Green / Q000378:metabolism; D041623:Tomography, Optical Coherence / Q000379:methods*
chemical_list: D007208:Indocyanine Green