| Literature DB >> 27435897 |
Simon S Gao1, Li Liu2, Steven T Bailey1, Christina J Flaxel1, David Huang1, Dengwang Li3, Yali Jia1.
Abstract
Quantification of choroidal neovascularization (CNV) as visualized by optical coherence tomography angiography (OCTA) may have importance clinically when diagnosing or tracking disease. Here, we present an automated algorithm to quantify the vessel skeleton of CNV as vessel length. Initial segmentation of the CNV on en face angiograms was achieved using saliency-based detection and thresholding. A level set method was then used to refine vessel edges. Finally, a skeleton algorithm was applied to identify vessel centerlines. The algorithm was tested on nine OCTA scans from participants with CNV and comparisons of the algorithm’s output to manual delineation showed good agreement.Entities:
Mesh:
Year: 2016 PMID: 27435897 PMCID: PMC4949375 DOI: 10.1117/1.JBO.21.7.076010
Source DB: PubMed Journal: J Biomed Opt ISSN: 1083-3668 Impact factor: 3.170