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Cited by 7Retinal Imaging and AnalysisRetinal Diseases and TreatmentsAdvanced Neural Network Applications

Advancing Diabetic Retinopathy Diagnosis: Leveraging Optical Coherence Tomography Imaging with Convolutional Neural Networks

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Kamil Yavuzer, Mehmet Çıtırık, Beyza Yavuzer·2023·romanian journal of ophthalmology
DOI 10.22336/rjo.2023.53PMC PMC10793365
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Abstract

Diabetic retinopathy (DR) is a vision-threatening complication of diabetes, necessitating early and accurate diagnosis.The combination of optical coherence tomography (OCT) imaging with convolutional neural networks (CNNs) has emerged as a promising approach for enhancing DR diagnosis.OCT provides detailed retinal morphology information, while CNNs analyze OCT images for automated detection and classification of DR.This paper reviews the current research on OCT imaging and CNNs for DR diagnosis, discussing their technical aspects and suitability.It explores CNN applications in detecting lesions, segmenting microaneurysms, and assessing disease severity, showing high sensitivity and accuracy.CNN models outperform traditional methods and rival expert ophthalmologists' results.However, challenges such as dataset availability and model interpretability remain.Future directions include multimodal imaging integration and realtime, point-of-care CNN systems for DR screening.The integration of OCT imaging with CNNs has transformative potential in DR diagnosis, facilitating early intervention, personalized treatments, and improved patient outcomes.

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References 44 · Cited by 7

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Authors
Yavuzer, K., Çıtırık, M., & Yavuzer, B.
Affiliations
Sağlık Bilimleri Üniversitesi (TR)
ORCID
Venue
romanian journal of ophthalmology
Publisher
Societatea Romana de Oftalmologie
Published
2023-12-15
Volume
67
Issue
4
Pages
326-336
ISSN
  • 2457-4325 (ISSN-L)
  • 2501-2533
DOI
10.22336/rjo.2023.53
PMC
PMC10793365
OpenAlex
W4390826298
Cited by
7
References
44
Citations by year
2026: 2 · 2025: 5
FWCI
1.16
Type
journal article
Language
en
Open access
Locations
  • Romanian Journal of Ophthalmology (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Retinal Imaging and Analysis
  • Health Sciences › Medicine › Ophthalmology › Retinal Diseases and Treatments
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
Keywords
diabetic retinopathy, optical coherence tomography, convolutional neural networks, automated disease detection, disease severity assessment, retinal lesion detection, multimodal imaging, point-of-care screening, data availability, model interpretability
MeSH terms
Fovea Centralis, Humans, Retina, Retinal Ganglion Cells, Retinitis Pigmentosa, Tomography, Optical Coherence

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