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

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorSahlsten, Jaakkoen_US
dc.contributor.authorJaskari, Joelen_US
dc.contributor.authorKivinen, Jyrien_US
dc.contributor.authorTurunen, Laurien_US
dc.contributor.authorJaanio, Esaen_US
dc.contributor.authorHietala, Kustaaen_US
dc.contributor.authorKaski, Kimmoen_US
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.groupauthorKaski Kimmo groupen
dc.contributor.groupauthorCentre of Excellence in Computational Inference, COINen
dc.contributor.organizationDepartment of Computer Scienceen_US
dc.contributor.organizationDigifundus Ltd.en_US
dc.contributor.organizationCentral Finland Central Hospitalen_US
dc.date.accessioned2019-08-15T08:21:15Z
dc.date.available2019-08-15T08:21:15Z
dc.date.issued2019-12-01en_US
dc.description.abstractDiabetes 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.en
dc.description.versionPeer revieweden
dc.format.extent1-11
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationSahlsten, J, Jaskari, J, Kivinen, J, Turunen, L, Jaanio, E, Hietala, K & Kaski, K 2019, ' Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading ', Scientific Reports, vol. 9, no. 1, 10750, pp. 1-11 . https://doi.org/10.1038/s41598-019-47181-wen
dc.identifier.doi10.1038/s41598-019-47181-wen_US
dc.identifier.issn2045-2322
dc.identifier.otherPURE UUID: 2274283c-754b-4fad-953f-81386a5be812en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/2274283c-754b-4fad-953f-81386a5be812en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85069691697&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/36027455/s41598_019_47181_w.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/39635
dc.identifier.urnURN:NBN:fi:aalto-201908154680
dc.language.isoenen
dc.publisherNATURE PUBLISHING GROUP
dc.relation.ispartofseriesScientific Reportsen
dc.relation.ispartofseriesVolume 9, issue 1en
dc.rightsopenAccessen
dc.titleDeep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Gradingen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion
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