⌘+K

Pulse Explore Communities Researchers Journals

Home Communities Explore

April 10, 2026Translational Vision Science & TechnologyOpen Access

The Application of a Deep Learning Algorithm for the Segmentation of Retinal Nerve Fiber Layer Across Different Optic Neuropathies

Roya Arian M. Shayesteh Far Reza Sadeghi Farshad Farnaghi Mona Safizadeh Prem S. Subramanian Neil R. Miller Yanin Suwan Pitchapa Kajornrojanaruk Raheleh Kafieh Masoud Aghsaei Fard

View Full Paper

Ask AI

Bookmark

Share

Key Points

The central aim is to evaluate the effectiveness of a deep learning algorithm in segmenting retinal nerve fiber layer thickness in various optic neuropathies.
Utilized a deep learning algorithm for analysis of retinal nerve fiber layer
Conducted measurements of RNFL thickness
Compared RNFL thickness results against ground truth data in cases of glaucoma and optic disc edema.
RNFL thickness measurements using RNFL-Net matched the established ground truth
Demonstrated accuracy in glaucoma and optic disc edema cases.

Ask about this paper

Answers are grounded in this paper and cite their sources.

Ask your own question…

Implication

Demonstrates effective segmentation of retinal nerve fiber layer in optic neuropathies, indicating potential for diagnosis.

Abstract

RNFL thickness measurements from RNFL-Net matched the ground truth in glaucoma and optic disc edema cases.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Arian et al. (2026) studied this question.

synapsesocial.com/papers/69db37ca4fe01fead37c5c8c https://doi.org/10.1167/tvst.15.4.7

View Full Paper

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Deep learning for predicting circular retinal nerve fiber layer thickness from fundus photographs and diagnosing glaucoma2024 · 10 citations
2Deep Learning-Based Generation of Retinal Nerve Fibre Layer Thickness Maps from Fundus Photographs: A Comparative Analysis of U-Net Architectures for Accessible Glaucoma AssessmentOriginal Research · 2026
3Deep Learning for Optic Disc Segmentation and Glaucoma Diagnosis on Retinal ImagesOriginal Research · 2020 · 184 citations
4Development of a Deep Learning-Based Algorithm for Detection and Analysis of Retinal Fluid Regions in OCT ImagesOriginal Research · 2026
5Segmentation of Retinal Layers in OCT Images Using Deep Learning MethodsOriginal Research · 2026

Optimizing Glaucoma Diagnosis with Deep Learning-Based Segmentation and Classification of Retinal Images2024
Automatic Optic Nerve Segmentation in Retinal Photographs for Glaucoma Detection Using Convolutional Neural Network2026
Deep Learning Techniques for Retinal Layer Segmentation to Aid Ocular Disease Diagnosis: A Review2025
Variations in Corneal Refractive Change Region After Orthokeratology Lens WearTranslational Vision Science & Technology · 2026
Association of Thyroid Autoimmunity With Age-Related Macular Degeneration in U.S. AdultsTranslational Vision Science & Technology · 2026

More from Translational Vision Science & Technology

More from Durham University

More from Johns Hopkins Hospital

More from Mahidol University

More from Tehran University of Medical Sciences

More from Ramathibodi Hospital

More from Farabi Hospital