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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9914068/ https://www.ncbi.nlm.nih.gov/pubmed/36766451 http://dx.doi.org/10.3390/diagnostics13030345 |
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author | Sebastian, Anila Elharrouss, Omar Al-Maadeed, Somaya Almaadeed, Noor |
author_facet | Sebastian, Anila Elharrouss, Omar Al-Maadeed, Somaya Almaadeed, Noor |
author_sort | Sebastian, Anila |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-9914068 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99140682023-02-11 A Survey on Deep-Learning-Based Diabetic Retinopathy Classification Sebastian, Anila Elharrouss, Omar Al-Maadeed, Somaya Almaadeed, Noor Diagnostics (Basel) Review 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. MDPI 2023-01-18 /pmc/articles/PMC9914068/ /pubmed/36766451 http://dx.doi.org/10.3390/diagnostics13030345 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Sebastian, Anila Elharrouss, Omar Al-Maadeed, Somaya Almaadeed, Noor A Survey on Deep-Learning-Based Diabetic Retinopathy Classification |
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 | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9914068/ https://www.ncbi.nlm.nih.gov/pubmed/36766451 http://dx.doi.org/10.3390/diagnostics13030345 |
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