Brennan Brea D, Heitkotter Heather, Carroll Joseph, Tarima Sergey, Cooper Robert F
Joint Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Department of Cell Biology, Neurobiology & Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Biomed Opt Express. 2024 Apr 4;15(5):2849-2862. doi: 10.1364/BOE.516477. eCollection 2024 May 1.
The use of "quality" to describe the usefulness of an image is ubiquitous but is often subject to domain specific constraints. Despite its continued use as an imaging modality, adaptive optics scanning light ophthalmoscopy (AOSLO) lacks a dedicated metric for quantifying the quality of an image of photoreceptors. Here, we present an approach to evaluating image quality that extracts an estimate of the signal to noise ratio. We evaluated its performance in 528 images of photoreceptors from two AOSLOs, two modalities, and healthy or diseased retinas. The algorithm was compared to expert graders' ratings of the images and previously published image quality metrics. We found no significant difference in the SNR and grades across all conditions. The SNR and the grades of the images were moderately correlated. Overall, this algorithm provides an objective measure of image quality that closely relates to expert assessments of quality in both confocal and split-detector AOSLO images of photoreceptors.
用“质量”来描述图像的有用性很普遍,但往往受到特定领域的限制。尽管自适应光学扫描光检眼镜(AOSLO)作为一种成像方式仍在持续使用,但其缺乏用于量化光感受器图像质量的专用指标。在此,我们提出一种评估图像质量的方法,该方法可提取信噪比的估计值。我们在来自两台AOSLO、两种模式以及健康或患病视网膜的528张光感受器图像中评估了其性能。将该算法与专家对图像的评分以及先前发表的图像质量指标进行了比较。我们发现在所有条件下,信噪比和评分均无显著差异。图像的信噪比与评分呈中度相关。总体而言,该算法提供了一种客观的图像质量测量方法,与专家对共焦和分探测器AOSLO光感受器图像质量的评估密切相关。