title: Vessel boundary delineation on fundus images using graph-based approach.
abstract: This paper proposes an algorithm to measure the width of retinal vessels in fundus photographs using graph-based algorithm to segment both vessel edges simultaneously. First, the simultaneous two-boundary segmentation problem is modeled as a two-slice, 3-D surface segmentation problem, which is further converted into the problem of computing a minimum closed set in a node-weighted graph. An initial segmentation is generated from a vessel probability image. We use the REVIEW database to evaluate diameter measurement performance. The algorithm is robust and estimates the vessel width with subpixel accuracy. The method is used to explore the relationship between the average vessel width and the distance from the optic disc in 600 subjects.
authors.affiliation: Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA.
authors.forename: Xiayu
authors.initials: X
authors.lastname: Xu
authors.forename: Meindert
authors.initials: M
authors.lastname: Niemeijer
authors.forename: Qi
authors.initials: Q
authors.lastname: Song
authors.forename: Milan
authors.initials: M
authors.lastname: Sonka
authors.forename: Mona K
authors.initials: MK
authors.lastname: Garvin
authors.forename: Joseph M
authors.initials: JM
authors.lastname: Reinhardt
authors.forename: Michael D
authors.initials: MD
authors.lastname: Abràmoff
mesh_terms: D000465:Algorithms; D003930:Diabetic Retinopathy / Q000473:pathology*; D005451:Fluorescein Angiography / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012171:Retinal Vessels / Q000473:pathology*; D042262:Retinoscopy / Q000379:methods; D012680:Sensitivity and Specificity