Photodiagnosis with deep learning: A GAN and autoencoder-based approach for diabetic retinopathy detection

Photodiagnosis with deep learning: A GAN and autoencoder-based approach for diabetic retinopathy detection

Background: Diabetic retinopathy (DR) is a leading cause of visual impairment and blindness worldwide, necessitating early detection and accurate diagnosis. This study proposes a novel framework integrating Generative Adversarial Networks (GANs) for data augmentation, denoising autoencoders for nois...

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Bibliographic Details
Main Authors: Kerem GENCER, Gülcan GENCER, Tuğçe Horozoğlu CERAN, Aynur ER BİLİR, Mustafa DOĞAN
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Photodiagnosis and Photodynamic Therapy
Subjects:
Diabetic retinopathy
Generative adversarial networks (GANs)
Denoising autoencoders
Transfer learning
Medical image analysis
Photodiagnosis
Online Access:http://www.sciencedirect.com/science/article/pii/S157210002500081X
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http://www.sciencedirect.com/science/article/pii/S157210002500081X

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