Resolution enhancement of wide-field interferometric microscopy by coupled deep autoencoders

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buir.contributor.authorÖzbay, Ekmel
buir.contributor.authorTurhan, Adil Burak
buir.contributor.orcidÖzbay, Ekmel|0000-0003-2953-1828
dc.citation.epage2552en_US
dc.citation.issueNumber10en_US
dc.citation.spage2545en_US
dc.citation.volumeNumber57en_US
dc.contributor.authorIşıl, Ç.en_US
dc.contributor.authorYorulmaz, M.en_US
dc.contributor.authorSolmaz, B.en_US
dc.contributor.authorTurhan, Adil Buraken_US
dc.contributor.authorYurdakul, C.en_US
dc.contributor.authorÜnlü, S.en_US
dc.contributor.authorÖzbay, Ekmelen_US
dc.contributor.authorKoç, A.en_US
dc.date.accessioned2019-02-21T16:07:39Z
dc.date.available2019-02-21T16:07:39Z
dc.date.issued2018en_US
dc.departmentNanotechnology Research Center (NANOTAM)en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.departmentDepartment of Physicsen_US
dc.description.abstractWide-field interferometric microscopy is a highly sensitive, label-free, and low-cost biosensing imaging technique capable of visualizing individual biological nanoparticles such as viral pathogens and exosomes. However, further resolution enhancement is necessary to increase detection and classification accuracy of subdiffraction-limited nanoparticles. In this study, we propose a deep-learning approach, based on coupled deep autoencoders, to improve resolution of images of L-shaped nanostructures. During training, our method utilizes microscope image patches and their corresponding manual truth image patches in order to learn the transformation between them. Following training, the designed network reconstructs denoised and resolution-enhanced image patches for unseen input.
dc.identifier.doi10.1364/AO.57.002545
dc.identifier.issn1559-128X
dc.identifier.urihttp://hdl.handle.net/11693/50375
dc.language.isoEnglish
dc.publisherOSA - The Optical Society
dc.relation.isversionofhttps://doi.org/10.1364/AO.57.002545
dc.source.titleApplied Opticsen_US
dc.titleResolution enhancement of wide-field interferometric microscopy by coupled deep autoencodersen_US
dc.typeArticleen_US

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