title: Improving vessel segmentation in ultra-wide field-of-view retinal fluorescein angiograms.
abstract: Vessel segmentation on ultra-wide field-of-view fluorescein angiogram sequences of the retina is a challenging problem. Vessel appearance undergoes severe changes, as different portions of the vascular structure become perfused in different frames. This paper presents a method for segmenting vessels in such sequences using steerable filters and automatic thresholding. We introduce a penalization stage on regions with high vessel response in the filtered image, improving the detection of peripheral vessels and reducing false positives around the optic disc and in regions of choroidal vessels and lesions. Quantitative results are provided, in which the penalization stage improves the segmentation precision segmentation by 11.84%, the recall by 12.98% and the accuracy by 0.40%. To facilitate further evaluation, usage, and algorithm comparison, the algorithm, the data set used, the ground truth, and the results are made available on the internet.
authors.affiliation: School of Computing, University of Dundee, Scotland. arovirez@computing.dundee.ac.uk
authors.forename: A
authors.initials: A
authors.lastname: Perez-Rovira
authors.forename: K
authors.initials: K
authors.lastname: Zutis
authors.forename: J P
authors.initials: JP
authors.lastname: Hubschman
authors.forename: E
authors.initials: E
authors.lastname: Trucco
mesh_terms: D000465:Algorithms; D005451:Fluorescein Angiography / Q000379:methods*; D006801:Humans; D015203:Reproducibility of Results; D012171:Retinal Vessels / Q000033:anatomy & histology*