| Literature DB >> 26417524 |
Li Liu1, Simon S Gao2, Steven T Bailey2, David Huang2, Dengwang Li3, Yali Jia2.
Abstract
Optical coherence tomography angiography has recently been used to visualize choroidal neovascularization (CNV) in participants with age-related macular degeneration. Identification and quantification of CNV area is important clinically for disease assessment. An automated algorithm for CNV area detection is presented in this article. It relies on denoising and a saliency detection model to overcome issues such as projection artifacts and the heterogeneity of CNV. Qualitative and quantitative evaluations were performed on scans of 7 participants. Results from the algorithm agreed well with manual delineation of CNV area.Entities:
Keywords: (100.0100) Image processing; (170.3880) Medical and biological imaging; (170.4500) Optical coherence tomography
Year: 2015 PMID: 26417524 PMCID: PMC4574680 DOI: 10.1364/BOE.6.003564
Source DB: PubMed Journal: Biomed Opt Express ISSN: 2156-7085 Impact factor: 3.732