Automatic Retinal Nerve Fiber Segmentation and the Influence of Intersubject Variability in Ocular Parameters on the Mapping of Retinal Sites to the Pointwise Orientation Angles
Diego Luján Villarreal, Adriana Leticia Vera-Tizatl

TL;DR
This study shows how differences between people's eye structures affect how retinal nerve fibers are mapped to visual field locations, using a new segmentation algorithm.
Contribution
A novel algorithm for retinal nerve fiber segmentation is introduced, and intersubject variability's impact on retinal mapping is quantified.
Findings
The PES algorithm achieved 97.6% accuracy in tracing retinal nerve fiber bundles.
The ONH-fovea angle and ONH position were the strongest predictors of mapping variability.
Significant individual variability was found, with standard deviations up to 44.05° across visual field locations.
Abstract
The current study investigates the influence of intersubject variability in ocular characteristics on the mapping of visual field (VF) sites to the pointwise directional angles in retinal nerve fiber layer (RNFL) bundle traces. In addition, the performance efficacy on the mapping of VF sites to the optic nerve head (ONH) was compared to ground truth baselines. Fundus photographs of 546 eyes of 546 healthy subjects (with no history of ocular disease or diabetic retinopathy) were enhanced digitally and RNFL bundle traces were segmented based on the Personalized Estimated Segmentation (PES) algorithm’s core technique. A 24-2 VF grid pattern was overlaid onto the photographs in order to relate VF test points to intersecting RNFL bundles. The PES algorithm effectively traced RNFL bundles in fundus images, achieving an average accuracy of 97.6% relative to the Jansonius map through the…
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Taxonomy
TopicsRetinal Imaging and Analysis · Retinal Diseases and Treatments · Retinal and Macular Surgery
