Evaluating the Impact of Retinal Vessel Segmentation Metrics on Retest Reliability in a Clinical Setting: A Comparative Analysis Using AutoMorph.

ABSTRACT:

Purpose

Current research on artificial intelligence-based fundus photography biomarkers has demonstrated inconsistent results. Consequently, we aimed to evaluate and predict the test-retest reliability of retinal parameters extracted from fundus photography.

Methods

Two groups of patients were recruited for the study: an intervisit group (n = 28) to assess retest reliability over a period of 1 to 14 days and an intravisit group (n = 44) to evaluate retest reliability within a single session. Using AutoMorph, we generated test and retest vessel segmentation maps; measured segmentation map agreement via accuracy, sensitivity, F1 score and Jaccard index; and calculated 76 metrics from each fundus image. The retest reliability of each metric was analyzed in terms of the Spearman

SUBMITTER: Giesser SD 

PROVIDER: S-EPMC11572755 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature