title: Feasibility of level-set analysis of enface OCT retinal images in diabetic retinopathy.
abstract: Pathology segmentation in retinal images of patients with diabetic retinopathy is important to help better understand disease processes. We propose an automated level-set method with Fourier descriptor-based shape priors. A cost function measures the difference between the current and expected output. We applied our method to enface images generated for seven retinal layers and determined correspondence of pathologies between retinal layers. We compared our method to a distance-regularized level set method and show the advantages of using well-defined shape priors. Results obtained allow us to observe pathologies across multiple layers and to obtain metrics that measure the co-localization of pathologies in different layers.
authors.affiliation: Department of Electrical and Computer Engineering, University of Illinois at Chicago, USA.
authors.forename: Fatimah
authors.initials: F
authors.lastname: Mohammad
authors.affiliation: Department of Electrical and Computer Engineering, University of Illinois at Chicago, USA.
authors.forename: Rashid
authors.initials: R
authors.lastname: Ansari
authors.affiliation: Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, USA.
authors.forename: Justin
authors.initials: J
authors.lastname: Wanek
authors.affiliation: Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, USA.
authors.forename: Andrew
authors.initials: A
authors.lastname: Francis
authors.affiliation: Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, USA.
authors.forename: Mahnaz
authors.initials: M
authors.lastname: Shahidi
keywords: (100.0100) Image processing; (100.2960) Image analysis; (170.4500) Optical coherence tomography