Open AccessAutomated detection of shadow artifacts in optical coherence tomography angiography
Author(s) -
Acner Camino,
Yali Jia,
Jeffrey Yu,
Jie Wang,
Liang Liu,
David Huang
Publication year - 2019
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.10.001514
Subject(s) - optical coherence tomography , retinal , optical coherence tomography angiography , diabetic retinopathy , shadow (psychology) , medicine , ophthalmology , macular degeneration , angiography , fluorescein angiography , tomography , optometry , retina , computer science , radiology , optics , physics , diabetes mellitus , psychology , psychotherapist , endocrinology
Frequently, when imaging retinal vasculature with optical coherence tomography angiography (OCTA) in diseased eyes, there are unavoidable obstacles to the propagation of light such as vitreous floaters or the pupil boundary. These obstacles can block the optical coherence tomography (OCT) beam and impede the visualization of the underlying retinal microcirculation. Detecting these shadow artifacts is especially important in the quantification of metrics that assess retinal disease progression because they might masquerade as regional perfusion loss. In this work, we present an algorithm to identify shadowed areas in OCTA of healthy subjects as well as patients with diabetic retinopathy, uveitis and age-related macular degeneration. The aim is to exclude these areas from analysis so that the overall OCTA parameters are minimally affected by shadow artifacts.