| Literature DB >> 28432113 |
Justis P Ehlers1, Kevin Wang1,2, Amit Vasanji3, Ming Hu1,4, Sunil K Srivastava1.
Abstract
Ultra-widefield fluorescein angiography (UWFA) is an emerging imaging modality used to characterise pathology in the retinal vasculature such as microaneurysms (MAs) and vascular leakage. Despite its potential value for diagnosis and disease surveillance, objective quantitative assessment of retinal pathology by UWFA is currently limited because it requires laborious manual segmentation by trained human graders. In this report, we describe a novel fully automated software platform, which segments MAs and leakage areas in native and dewarped UWFA images with retinal vascular disease. Comparison of the algorithm with human grader-generated gold standards demonstrated significant strong correlations for MA and leakage areas (intraclass correlation coefficient (ICC)=0.78-0.87 and ICC=0.70-0.86, respectively, p=2.1×10-7 to 3.5×10-10 and p=7.8×10-6 to 1.3×10-9, respectively). These results suggest the algorithm performs similarly to human graders in MA and leakage segmentation and may be of significant utility in clinical and research settings. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.Entities:
Keywords: Diagnostic tests/Investigation; Imaging; Macula; Retina
Mesh:
Year: 2017 PMID: 28432113 PMCID: PMC5512291 DOI: 10.1136/bjophthalmol-2016-310047
Source DB: PubMed Journal: Br J Ophthalmol ISSN: 0007-1161 Impact factor: 4.638