Retinal Disease Detection and Classification Using Convolution Neural Networks and Transfer Learning

DOI

10.2991/978-94-6463-754-0_61How to use a DOI?

Keywords

OCT images; CNN; transfer learning; deep learning; feature extraction

Abstract

The categorization of retinal diseases utilizing Optical Coherence Tomography (OCT) images has garnered considerable interest in the domain of computational medical imaging. This research paper introduces a deep learning methodology for the automated classification of OCT images via a custom Convolution Neural Network (CNN) in conjunction with recognized transfer learning models. Deep learning methodologies are favored for their exceptional accuracy and performance; however, they frequently necessitate substantial computational resources and time for training. MobileNet, ResNet50, GoogleNet, and DenseNet are employed for feature extraction and comparison analysis. The models are trained and refined on an OCT dataset utilizing various hyperparameter settings, such as learning rate, epoch count, and optimizing techniques to get maximal accuracy. Upon concluding our study, the performance of these models is evaluated, and the optimal design is ascertained based on accuracy and additional assessment criteria. Our methodology illustrates the capability of deep learning in the automated classification of OCT images, providing enhanced diagnostic support for the identification of retinal diseases.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Aditya Agarwal
AU  - Rohan Gupta
AU  - Abhinav Panwar
AU  - R. Loganathan
AU  - S. Latha
AU  - P. Muthu
AU  - Samiappan Dhanalakshmi
PY  - 2025
DA  - 2025/06/30
TI  - Retinal Disease Detection and Classification Using Convolution Neural Networks and Transfer Learning
BT  - Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025)
PB  - Atlantis Press
SP  - 702
EP  - 715
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-754-0_61
DO  - 10.2991/978-94-6463-754-0_61
ID  - Agarwal2025
ER  -