Automated Assessment of Photoreceptor Visibility in Adaptive Optics Split-Detection Images Using Edge Detection.

ABSTRACT:

Purpose

Adaptive optics scanning laser ophthalmoscopy (AOSLO) is a high-resolution imaging modality that allows measurements of cellular-level retinal changes in living patients. In retinal diseases, the visibility of photoreceptors in AOSLO images is affected by pathology, patient motion, and optics, which can lead to variability in analyses of the photoreceptor mosaic. Current best practice for AOSLO mosaic quantification requires manual assessment of photoreceptor visibility across overlapping images, a laborious and time-consuming task.

Methods

We propose an automated measure for quantification of photoreceptor visibility in AOSLO. Our method detects salient edge features, which can represent visible photoreceptor boundaries in each image. We evaluate our measure against

SUBMITTER: Chen M 

PROVIDER: S-EPMC9145033 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature