Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading

Abstract Diabetes is a globally prevalent disease that can cause visible microvascular complications such as diabetic retinopathy and macular edema in the human eye retina, the images of which are today used for manual disease screening and diagnosis. This labor-intensive task could greatly benefit...

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Autores principales:	Jaakko Sahlsten, Joel Jaskari, Jyri Kivinen, Lauri Turunen, Esa Jaanio, Kustaa Hietala, Kimmo Kaski
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7be95b5c7f1c4b319f24496ec35ec514
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spelling	oai:doaj.org-article:7be95b5c7f1c4b319f24496ec35ec5142021-12-02T15:09:47ZDeep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading10.1038/s41598-019-47181-w2045-2322https://doaj.org/article/7be95b5c7f1c4b319f24496ec35ec5142019-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-019-47181-whttps://doaj.org/toc/2045-2322Abstract Diabetes is a globally prevalent disease that can cause visible microvascular complications such as diabetic retinopathy and macular edema in the human eye retina, the images of which are today used for manual disease screening and diagnosis. This labor-intensive task could greatly benefit from automatic detection using deep learning technique. Here we present a deep learning system that identifies referable diabetic retinopathy comparably or better than presented in the previous studies, although we use only a small fraction of images (<1/4) in training but are aided with higher image resolutions. We also provide novel results for five different screening and clinical grading systems for diabetic retinopathy and macular edema classification, including state-of-the-art results for accurately classifying images according to clinical five-grade diabetic retinopathy and for the first time for the four-grade diabetic macular edema scales. These results suggest, that a deep learning system could increase the cost-effectiveness of screening and diagnosis, while attaining higher than recommended performance, and that the system could be applied in clinical examinations requiring finer grading.Jaakko SahlstenJoel JaskariJyri KivinenLauri TurunenEsa JaanioKustaa HietalaKimmo KaskiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 9, Iss 1, Pp 1-11 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jaakko Sahlsten Joel Jaskari Jyri Kivinen Lauri Turunen Esa Jaanio Kustaa Hietala Kimmo Kaski Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading
description	Abstract Diabetes is a globally prevalent disease that can cause visible microvascular complications such as diabetic retinopathy and macular edema in the human eye retina, the images of which are today used for manual disease screening and diagnosis. This labor-intensive task could greatly benefit from automatic detection using deep learning technique. Here we present a deep learning system that identifies referable diabetic retinopathy comparably or better than presented in the previous studies, although we use only a small fraction of images (<1/4) in training but are aided with higher image resolutions. We also provide novel results for five different screening and clinical grading systems for diabetic retinopathy and macular edema classification, including state-of-the-art results for accurately classifying images according to clinical five-grade diabetic retinopathy and for the first time for the four-grade diabetic macular edema scales. These results suggest, that a deep learning system could increase the cost-effectiveness of screening and diagnosis, while attaining higher than recommended performance, and that the system could be applied in clinical examinations requiring finer grading.
format	article
author	Jaakko Sahlsten Joel Jaskari Jyri Kivinen Lauri Turunen Esa Jaanio Kustaa Hietala Kimmo Kaski
author_facet	Jaakko Sahlsten Joel Jaskari Jyri Kivinen Lauri Turunen Esa Jaanio Kustaa Hietala Kimmo Kaski
author_sort	Jaakko Sahlsten
title	Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading
title_short	Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading
title_full	Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading
title_fullStr	Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading
title_full_unstemmed	Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading
title_sort	deep learning fundus image analysis for diabetic retinopathy and macular edema grading
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/7be95b5c7f1c4b319f24496ec35ec514
work_keys_str_mv	AT jaakkosahlsten deeplearningfundusimageanalysisfordiabeticretinopathyandmacularedemagrading AT joeljaskari deeplearningfundusimageanalysisfordiabeticretinopathyandmacularedemagrading AT jyrikivinen deeplearningfundusimageanalysisfordiabeticretinopathyandmacularedemagrading AT lauriturunen deeplearningfundusimageanalysisfordiabeticretinopathyandmacularedemagrading AT esajaanio deeplearningfundusimageanalysisfordiabeticretinopathyandmacularedemagrading AT kustaahietala deeplearningfundusimageanalysisfordiabeticretinopathyandmacularedemagrading AT kimmokaski deeplearningfundusimageanalysisfordiabeticretinopathyandmacularedemagrading
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Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading

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