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Quantifying image quality in AOSLO images of photoreceptors. Biomed Opt Express 2024 May 01;15(5):2849-2862

Date

06/10/2024

Pubmed ID

38855680

Pubmed Central ID

PMC11161361

DOI

10.1364/BOE.516477

Scopus ID

2-s2.0-85192472866 (requires institutional sign-in at Scopus site)   1 Citation

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.

Author List

Brennan BD, Heitkotter H, Carroll J, Tarima S, Cooper RF

Authors

Joseph J. Carroll PhD Director, Professor in the Ophthalmology and Visual Sciences department at Medical College of Wisconsin
Robert F. Cooper Ph.D Assistant Professor in the Biomedical Engineering department at Marquette University
Sergey S. Tarima PhD Associate Professor in the Data Science Institute department at Medical College of Wisconsin