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Article: Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review

TitleAdvances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review
Authors
KeywordsArtificial intelligence
Deep learning
Diabetic retinopathy
Optical coherence tomography
Retina
Issue Date2018
PublisherSpringer (part of Springer Nature): Fully open access journals - CC BY-NC. The Journal's web site is located at https://link.springer.com/journal/40123
Citation
Ophthalmology and Therapy, 2018, v. 7 n. 2, p. 333-346 How to Cite?
AbstractRising prevalence of diabetes worldwide has necessitated the implementation of population-based diabetic retinopathy (DR) screening programs that can perform retinal imaging and interpretation for extremely large patient cohorts in a rapid and sensitive manner while minimizing inappropriate referrals to retina specialists. While most current screening programs employ mydriatic or nonmydriatic color fundus photography and trained image graders to identify referable DR, new imaging modalities offer significant improvements in diagnostic accuracy, throughput, and affordability. Smartphone-based fundus photography, macular optical coherence tomography, ultrawide-field imaging, and artificial intelligence-based image reading address limitations of current approaches and will likely become necessary as DR becomes more prevalent. Here we review current trends in imaging for DR screening and emerging technologies that show potential for improving upon current screening approaches.
Persistent Identifierhttp://hdl.handle.net/10722/277429
ISSN
2023 Impact Factor: 2.6
2023 SCImago Journal Rankings: 1.158
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorFenner, BJ-
dc.contributor.authorWong, RLM-
dc.contributor.authorLam, WC-
dc.contributor.authorTan, GSW-
dc.contributor.authorCheung, GCM-
dc.date.accessioned2019-09-20T08:50:54Z-
dc.date.available2019-09-20T08:50:54Z-
dc.date.issued2018-
dc.identifier.citationOphthalmology and Therapy, 2018, v. 7 n. 2, p. 333-346-
dc.identifier.issn2193-8245-
dc.identifier.urihttp://hdl.handle.net/10722/277429-
dc.description.abstractRising prevalence of diabetes worldwide has necessitated the implementation of population-based diabetic retinopathy (DR) screening programs that can perform retinal imaging and interpretation for extremely large patient cohorts in a rapid and sensitive manner while minimizing inappropriate referrals to retina specialists. While most current screening programs employ mydriatic or nonmydriatic color fundus photography and trained image graders to identify referable DR, new imaging modalities offer significant improvements in diagnostic accuracy, throughput, and affordability. Smartphone-based fundus photography, macular optical coherence tomography, ultrawide-field imaging, and artificial intelligence-based image reading address limitations of current approaches and will likely become necessary as DR becomes more prevalent. Here we review current trends in imaging for DR screening and emerging technologies that show potential for improving upon current screening approaches.-
dc.languageeng-
dc.publisherSpringer (part of Springer Nature): Fully open access journals - CC BY-NC. The Journal's web site is located at https://link.springer.com/journal/40123-
dc.relation.ispartofOphthalmology and Therapy-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectArtificial intelligence-
dc.subjectDeep learning-
dc.subjectDiabetic retinopathy-
dc.subjectOptical coherence tomography-
dc.subjectRetina-
dc.titleAdvances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review-
dc.typeArticle-
dc.identifier.emailLam, WC: waichlam@hku.hk-
dc.identifier.authorityLam, WC=rp02162-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1007/s40123-018-0153-7-
dc.identifier.scopuseid_2-s2.0-85063258684-
dc.identifier.hkuros305717-
dc.identifier.volume7-
dc.identifier.issue2-
dc.identifier.spage333-
dc.identifier.epage346-
dc.identifier.isiWOS:000452599200011-
dc.publisher.placeNew Zealand-
dc.identifier.issnl2193-8245-

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