ArticleComputational intelligence and neuroscience2022
Diagnosis of Retinal Diseases Based on Bayesian Optimization Deep Learning Network Using Optical Coherence Tomography Images.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- A Low Complexity Efficient Deep Learning Model for Automated Retinal Disease Diagnosis.Journal of healthcare informatics research · 2025Article
- Multimodal deep transfer learning to predict retinal vein occlusion macular edema recurrence after anti-VEGF therapy.Heliyon · 2024Article
- Article
- Evaluating Retinal Disease Diagnosis with an Interpretable Lightweight CNN Model Resistant to Adversarial Attacks.Journal of imaging · 2023Article
- Multi-Fundus Diseases Classification Using Retinal Optical Coherence Tomography Images with Swin Transformer V2.Journal of imaging · 2023Article
- An interpretable transformer network for the retinal disease classification using optical coherence tomography.Scientific reports · 2023Article
- Diagnosing Breast Cancer Based on the Adaptive Neuro-Fuzzy Inference System.Computational and mathematical methods in medicine · 2022Article
- Computational and Mathematical Methods in Medicine Glioma Brain Tumor Detection and Classification Using Convolutional Neural Network.Computational and mathematical methods in medicine · 2022Article
- An Empirical Analysis of an Optimized Pretrained Deep Learning Model for COVID-19 Diagnosis.Computational and mathematical methods in medicine · 2022Article
- Analysis on COVID-19 Infection Spread Rate during Relief Schemes Using Graph Theory and Deep Learning.Computational and mathematical methods in medicine · 2022Article
- Multiconvolutional Transfer Learning for 3D Brain Tumor Magnetic Resonance Images.Computational intelligence and neuroscience · 2022Article
- Prediction of the Age and Gender Based on Human Face Images Based on Deep Learning Algorithm.Computational and mathematical methods in medicine · 2022Article
- Investigation of Applying Machine Learning and Hyperparameter Tuned Deep Learning Approaches for Arrhythmia Detection in ECG Images.Computational and mathematical methods in medicine · 2022Article
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7 authors.
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Abstract
Retinal abnormalities have emerged as a serious public health concern in recent years and can manifest gradually and without warning. These diseases can affect any part of the retina, causing vision impairment and indeed blindness in extreme cases. This necessitates the development of automated approaches to detect retinal diseases more precisely and, preferably, earlier. In this paper, we examine transfer learning of pretrained convolutional neural network (CNN) and then transfer it to detect retinal problems from Optical Coherence Tomography (OCT) images. In this study, pretrained CNN models, namely, VGG16, DenseNet201, InceptionV3, and Xception, are used to classify seven different retinal diseases from a dataset of images with and without retinal diseases. In addition, to choose optimum values for hyperparameters, Bayesian optimization is applied, and image augmentation is used to increase the generalization capabilities of the developed models. This research also provides a comparison of the proposed models as well as an analysis of them. The accuracy achieved using DenseNet201 on the Retinal OCT Image dataset is more than 99% and offers a good level of accuracy in classifying retinal diseases compared to other approaches, which only detect a small number of retinal diseases.
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