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Cited by 328

The DOI matches its Crossref record; 164 of the 164 references it cites were found in a registry or an index.

Deep learning for diabetic retinopathy detection and classification based on fundus images: A review

Open access
Tsiknakis, Nikos, Theodoropoulos, Dimitris, Manikis, Georgios, Ktistakis, Emmanouil, Boutsora, Ourania, Berto, Alexa, Scarpa, Fabio, Scarpa, Alberto, Fotiadis, Dimitrios I., Marias, Kostas·2021·Computers in Biology and Medicine

Abstract

Diabetic Retinopathy is a retina disease caused by diabetes mellitus and it is the leading cause of blindness globally. Early detection and treatment are necessary in order to delay or avoid vision deterioration and vision loss. To that end, many artificial-intelligence-powered methods have been proposed by the research community for the detection and classification of diabetic retinopathy on fundus retina images. This review article provides a thorough analysis of the use of deep learning methods at the various steps of the diabetic retinopathy detection pipeline based on fundus images. We discuss several aspects of that pipeline, ranging from the datasets that are widely used by the research community, the preprocessing techniques employed and how these accelerate and improve the models' performance, to the development of such deep learning models for the diagnosis and grading of the disease as well as the localization of the disease's lesions. We also discuss certain models that have been applied in real clinical settings. Finally, we conclude with some important insights and provide future research directions.

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Metadata

Authors
Tsiknakis, N., Theodoropoulos, D., Manikis, G., Ktistakis, E., Boutsora, O., Berto, A., Scarpa, F., Scarpa, A., Fotiadis, D. I., & Marias, K.
Venue
Computers in Biology and Medicine
Publisher
Elsevier BV
Published
2021-08
Volume
135
Pages
104599
ISSN
0010-4825 (ISSN-L)
OpenAlex
W3175311671
Cited by
328
References
164
FWCI
25.63
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Deep learning for diabetic retinopathy detection and classification based on fundus images: A review. https://app.cochat.ai/papers/10.1016/j.compbiomed.2021.104599
The paper
Tsiknakis, N., Theodoropoulos, D., Manikis, G., Ktistakis, E., Boutsora, O., Berto, A., Scarpa, F., Scarpa, A., Fotiadis, D. I., & Marias, K. (2021). Deep learning for diabetic retinopathy detection and classification based on fundus images: A review. Computers in Biology and Medicine. https://doi.org/10.1016/j.compbiomed.2021.104599

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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