Evaluating deep learning models for classifying OCT images with limited data and noisy labels

Evaluating deep learning models for classifying OCT images with limited data and noisy labels

Abstract The use of deep learning for OCT image classification could enhance the diagnosis and monitoring of retinal diseases. However, challenges like variability in retinal abnormalities, noise, and artifacts in OCT images limit its clinical use. Our study aimed to evaluate the performance of vari...

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Bibliographic Details
Main Authors: Aleksandar Miladinović, Alessandro Biscontin, Miloš Ajčević, Simone Kresevic, Agostino Accardo, Dario Marangoni, Daniele Tognetto, Leandro Inferrera
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Reports
Subjects:
OCT
CNN
Deep learning
Retina
Retinal imaging
Online Access:https://doi.org/10.1038/s41598-024-81127-1
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