透镜自光和变暗对视网膜成像的影响
Leon von der Emde1,2, Geena C Rennen1, Marc Vaisband3,4
1Department of Ophthalmology, University Hospital Bonn, Bonn, NRW, Germany.
BMJ open ophthalmology
|April 29, 2024
概括
镜头变暗显著影响视网膜成像质量,特别是蓝色/绿色底部自光 (FAF). 卷积神经网络 (CNN) 有效地评估图像质量,有助于可靠的视网膜疾病监测.
科学领域:
- 眼科和生物医学光学.
- 医学影像分析和人工智能.
背景情况:
- 视网膜成像质量非常依赖光学介质的清晰度.
- 老化的镜头会导致阻光和自发光,扭曲图像分析.
- 研究了镜头变暗和自流光 (AF) 度量,以确定它们对自动图像质量评估的影响.
研究的目的:
- 为了量化镜头不透明度和AF指标.
- 评估镜头指标对视网膜图像质量评估自动化的影响.
- 将自动化图像质量评估与人类分级进行比较.
主要方法:
- 在227名受试者身上进行了镜头定量AF (LQAF),Scheimpflug成像和前腔OCT.
- 使用LQAF值,Pentacam核分期得分和相对镜头反射率来估计镜头的阴暗度.
- 开发了一个卷积神经网络 (CNN) 来预测FAF和红外 (IR) 图像质量,结果与人类评估相关.
主要成果:
- 视网膜图像质量在所有模式 (IR > GAF > BAF) 中总体上很高.
- 基于CNN的图像质量预测显示出极好的准确性 (MAE 0.9),与人类分级相当.
- 镜头的定量AF (LQAF) 与图像质量标准的相关性最强,蓝/绿FAF (BAF) 对镜头更改最容易受到影响.
结论:
- 基于CNN的图像质量评估对视网膜成像非常有效.
- 镜片变暗显著影响BAF质量,需要在临床研究中考虑.
- 这些发现可以为可靠的视网膜疾病监测制定切断值.
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