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

Abstract Rising 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...
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Autor*in:	Fenner, Beau J. [verfasserIn] Wong, Raymond L. M. [verfasserIn] Lam, Wai-Ching [verfasserIn] Tan, Gavin S. W. [verfasserIn] Cheung, Gemmy C. M. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Artificial intelligence Deep learning Diabetic retinopathy Optical coherence tomography Retina Ultrawide field imaging

Anmerkung:	© The Author(s) 2018

Übergeordnetes Werk:	Enthalten in: Ophthalmology and therapy - Springer Healthcare, 2012, 7(2018), 2 vom: 10. Nov., Seite 333-346
Übergeordnetes Werk:	volume:7 ; year:2018 ; number:2 ; day:10 ; month:11 ; pages:333-346

Links:	Volltext

DOI / URN:	10.1007/s40123-018-0153-7

Katalog-ID:	SPR033011591

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source	Enthalten in Ophthalmology and therapy 7(2018), 2 vom: 10. Nov., Seite 333-346 volume:7 year:2018 number:2 day:10 month:11 pages:333-346
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topic_facet	Artificial intelligence Deep learning Diabetic retinopathy Optical coherence tomography Retina Ultrawide field imaging
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container_title	Ophthalmology and therapy
authorswithroles_txt_mv	Fenner, Beau J. @@aut@@ Wong, Raymond L. M. @@aut@@ Lam, Wai-Ching @@aut@@ Tan, Gavin S. W. @@aut@@ Cheung, Gemmy C. M. @@aut@@
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author	Fenner, Beau J.
spellingShingle	Fenner, Beau J. ddc 610 misc Artificial intelligence misc Deep learning misc Diabetic retinopathy misc Optical coherence tomography misc Retina misc Ultrawide field imaging Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review
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topic_title	610 VZ Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review Artificial intelligence (dpeaa)DE-He213 Deep learning (dpeaa)DE-He213 Diabetic retinopathy (dpeaa)DE-He213 Optical coherence tomography (dpeaa)DE-He213 Retina (dpeaa)DE-He213 Ultrawide field imaging (dpeaa)DE-He213
topic	ddc 610 misc Artificial intelligence misc Deep learning misc Diabetic retinopathy misc Optical coherence tomography misc Retina misc Ultrawide field imaging
topic_unstemmed	ddc 610 misc Artificial intelligence misc Deep learning misc Diabetic retinopathy misc Optical coherence tomography misc Retina misc Ultrawide field imaging
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title	Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review
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title_full	Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review
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title_sort	advances in retinal imaging and applications in diabetic retinopathy screening: a review
title_auth	Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review
abstract	Abstract Rising 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. © The Author(s) 2018
abstractGer	Abstract Rising 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. © The Author(s) 2018
abstract_unstemmed	Abstract Rising 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. © The Author(s) 2018
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title_short	Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review
url	https://dx.doi.org/10.1007/s40123-018-0153-7
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