Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography

Li Liu, Simon S. Gao, Steven T. Bailey, David Huang, Dengwang Li, Yali Jia

Research output: Contribution to journalArticle

62 Scopus citations

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.

Original languageEnglish (US)
Article numberA018
Pages (from-to)3564-3575
Number of pages12
JournalBiomedical Optics Express
Volume6
Issue number9
DOIs
StatePublished - Aug 25 2015

ASJC Scopus subject areas

  • Biotechnology
  • Atomic and Molecular Physics, and Optics

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