Hybrid optimization-enhanced deep learning for effective diabetic retinopathy classification using OCT images: A step towards accessible and affordable healthcare solutions-Reference-Cited by-同舟云学术

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Hybrid optimization-enhanced deep learning for effective diabetic retinopathy classification using OCT images: A step towards accessible and affordable healthcare solutions

Published:2025-11 Issue: Volume:109 Page:107920
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Krishnan Sangeetha,K Valarmathi

Publisher

Elsevier BV

Reference45 articles.

1. Precise higher-order reflectivity and morphology models for early diagnosis of diabetic retinopathy using OCT images;Sharafeldeen;Sci. Rep.,2021

2. Associations of retinal neurovascular dysfunction with inner retinal layer thickness in non-proliferative diabetic retinopathy;Pemp;Graefes Arch. Clin. Exp. Ophthalmol.,2024

3. Anti-VEGF therapy for the long-term management of diabetic macular edema: a treat-to-target strategy based on macular morphology;Nakao;Graefes Arch. Clin. Exp. Ophthalmol.,2024

4. Optical coherence tomography homography for detection of retinal displacement: a validation study;Brosh;Graefes Arch. Clin. Exp. Ophthalmol.,2024

5. Deep learning based early stage diabetic retinopathy detection using optical coherence tomography;Li;Neurocomputing,2019

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