光学相干断层扫描血管造影中阴影伪影的自动检测
Automated detection of shadow artifacts in optical coherence tomography angiography.
作者信息
Camino Acner, Jia Yali, Yu Jeffrey, Wang Jie, Liu Liang, Huang David
机构信息
Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA.
Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR 97239, USA.
出版信息
Biomed Opt Express. 2019 Feb 28;10(3):1514-1531. doi: 10.1364/BOE.10.001514. eCollection 2019 Mar 1.
Abstract
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.
摘要
在使用光学相干断层扫描血管造影（OCTA）对患病眼睛的视网膜血管系统进行成像时，经常会出现一些不可避免的光传播障碍，如玻璃体混浊或瞳孔边界。这些障碍会阻挡光学相干断层扫描（OCT）光束，妨碍对其下方视网膜微循环的观察。在评估视网膜疾病进展的指标量化过程中，检测这些阴影伪像尤为重要，因为它们可能会伪装成局部灌注损失。在这项工作中，我们提出了一种算法，用于识别健康受试者以及患有糖尿病性视网膜病变、葡萄膜炎和年龄相关性黄斑变性患者的OCTA中的阴影区域。目的是将这些区域排除在分析之外，以使整体OCTA参数受阴影伪像的影响最小。
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