Work

Feasibility of level-set analysis of enface OCT retinal images in diabetic retinopathy

Year: 2015

Type: article

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.

Source: Biomedical Optics Express

DOI: 10.1364/boe.6.001904

Authors: Fatimah Mohammad, Rashid Ansari, Justin Wanek, Andrew Francis, Mahnaz Shahidi

Institution: University of Illinois Chicago

Language: English

Topic: Retinal Imaging and Analysis

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,913