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Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603
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Abstract

Background

Diabetic Retinopathy is a growing problem in Asian countries. accounts for 5% to 7% of all blindness in the entire area. In India, the record of -affected patients will reach around 79.4 million by 2030.

Aims

The main objective of the investigation is to utilize 2-D colored fundus retina scans to determine if an individual possesses or not. In this regard, Engineering-based techniques such as deep learning and neural networks play a methodical role in fighting against this fatal disease.

Methods

In this research work, a Computational Model for detecting using Convolutional Neural Network (DRCNN) is proposed. This method contrasts the fundus retina scans of the -afflicted eye with the usual human eyes. Using CNN and layers like Conv2D, Pooling, Dense, Flatten, and Dropout, the model aids in comprehending the scan's curve and color-based features. For training and error reduction, the Visual Geometry Group (VGG-16) model and Adaptive Moment Estimation Optimizer are utilized.

Results

The variations in a dataset like 50%, 60%, 70%, 80%, and 90% images are reserved for the training phase, and the rest images are reserved for the testing phase. In the proposed model, model comprises 138M parameters. The accuracy is achieved maximum rate of 90% when the training dataset is reserved at 80%. The model was validated using other datasets.

Conclusion

The suggested contribution to research determines conclusively whether the provided OCT scan utilizes an effective method for detecting -affected individuals within just a few moments.

© 2024 The Author(s). Published by Bentham Science Publisher.
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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2024-01-01
2025-06-24

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/content/journals/cmir/10.2174/0115734056248183231010111937
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Computational Model for the Detection of Diabetic Retinopathy in 2-D Color Fundus Retina Scan
Curr. Med. Imaging 20, e15734056248183 (2024); https://doi.org/10.2174/0115734056248183231010111937
/content/journals/cmir/10.2174/0115734056248183231010111937
/content/journals/cmir/10.2174/0115734056248183231010111937
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  • Article Type:     Research Article
Keyword(s): 2-D fundus; Convolutional neural network; Diabetic retinopathy; Hyperglycemia; NPDR; Retina

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