Quantifying image quality in AOSLO images of photoreceptors

Abstract

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.