A Survey on Deep-Learning-Based Diabetic Retinopathy Classification
The number of people who suffer from diabetes in the world has been considerably increasing recently. It affects people of all ages. People who have had diabetes for a long time are affected by a condition called Diabetic Retinopathy (DR), which damages the eyes. Automatic detection using new techno...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/13/3/345 |
| _version_ | 1797624932662771712 |
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| author | Anila Sebastian Omar Elharrouss Somaya Al-Maadeed Noor Almaadeed |
| author_facet | Anila Sebastian Omar Elharrouss Somaya Al-Maadeed Noor Almaadeed |
| author_sort | Anila Sebastian |
| collection | DOAJ |
| description | The number of people who suffer from diabetes in the world has been considerably increasing recently. It affects people of all ages. People who have had diabetes for a long time are affected by a condition called Diabetic Retinopathy (DR), which damages the eyes. Automatic detection using new technologies for early detection can help avoid complications such as the loss of vision. Currently, with the development of Artificial Intelligence (AI) techniques, especially Deep Learning (DL), DL-based methods are widely preferred for developing DR detection systems. For this purpose, this study surveyed the existing literature on diabetic retinopathy diagnoses from fundus images using deep learning and provides a brief description of the current DL techniques that are used by researchers in this field. After that, this study lists some of the commonly used datasets. This is followed by a performance comparison of these reviewed methods with respect to some commonly used metrics in computer vision tasks. |
| first_indexed | 2024-03-11T09:49:39Z |
| format | Article |
| id | doaj.art-f721b479510145c6a678ddd26b20d935 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-11T09:49:39Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-f721b479510145c6a678ddd26b20d9352023-11-16T16:23:24ZengMDPI AGDiagnostics2075-44182023-01-0113334510.3390/diagnostics13030345A Survey on Deep-Learning-Based Diabetic Retinopathy ClassificationAnila Sebastian0Omar Elharrouss1Somaya Al-Maadeed2Noor Almaadeed3Department of Computer Science and Engineering, Qatar University, Doha P.O. Box 2713, QatarDepartment of Computer Science and Engineering, Qatar University, Doha P.O. Box 2713, QatarDepartment of Computer Science and Engineering, Qatar University, Doha P.O. Box 2713, QatarDepartment of Computer Science and Engineering, Qatar University, Doha P.O. Box 2713, QatarThe number of people who suffer from diabetes in the world has been considerably increasing recently. It affects people of all ages. People who have had diabetes for a long time are affected by a condition called Diabetic Retinopathy (DR), which damages the eyes. Automatic detection using new technologies for early detection can help avoid complications such as the loss of vision. Currently, with the development of Artificial Intelligence (AI) techniques, especially Deep Learning (DL), DL-based methods are widely preferred for developing DR detection systems. For this purpose, this study surveyed the existing literature on diabetic retinopathy diagnoses from fundus images using deep learning and provides a brief description of the current DL techniques that are used by researchers in this field. After that, this study lists some of the commonly used datasets. This is followed by a performance comparison of these reviewed methods with respect to some commonly used metrics in computer vision tasks.https://www.mdpi.com/2075-4418/13/3/345diabetic retinopathy gradingdiabetic retinopathy detectiondeep learningconvolutional neural networkretinal fundus images |
| spellingShingle | Anila Sebastian Omar Elharrouss Somaya Al-Maadeed Noor Almaadeed A Survey on Deep-Learning-Based Diabetic Retinopathy Classification Diagnostics diabetic retinopathy grading diabetic retinopathy detection deep learning convolutional neural network retinal fundus images |
| title | A Survey on Deep-Learning-Based Diabetic Retinopathy Classification |
| title_full | A Survey on Deep-Learning-Based Diabetic Retinopathy Classification |
| title_fullStr | A Survey on Deep-Learning-Based Diabetic Retinopathy Classification |
| title_full_unstemmed | A Survey on Deep-Learning-Based Diabetic Retinopathy Classification |
| title_short | A Survey on Deep-Learning-Based Diabetic Retinopathy Classification |
| title_sort | survey on deep learning based diabetic retinopathy classification |
| topic | diabetic retinopathy grading diabetic retinopathy detection deep learning convolutional neural network retinal fundus images |
| url | https://www.mdpi.com/2075-4418/13/3/345 |
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