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dc.contributor.authorAvci, Oguzhanen_US
dc.contributor.authorYurdakul, Celalettinen_US
dc.contributor.authorUnlu, M. Selimen_US
dc.date.accessioned2019-09-06T18:52:45Z
dc.date.available2019-09-06T18:52:45Z
dc.date.issued2017-05-20
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000401839000002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=6e74115fe3da270499c3d65c9b17d654
dc.identifier.citationOguzhan Avci, Celalettin Yurdakul, M Selim Unlu. 2017. "Nanoparticle classification in wide-field interferometric microscopy by supervised learning from model." APPLIED OPTICS, Volume 56, Issue 15, pp. 4238 - 4242 (5). https://doi.org/10.1364/AO.56.004238
dc.identifier.issn1559-128X
dc.identifier.issn2155-3165
dc.identifier.urihttps://hdl.handle.net/2144/37746
dc.description.abstractInterference-enhanced wide-field nanoparticle imaging is a highly sensitive technique that has found numerous applications in labeled and label-free subdiffraction-limited pathogen detection. It also provides unique opportunities for nanoparticle classification upon detection. More specifically, the nanoparticle defocus images result in a particle-specific response that can be of great utility for nanoparticle classification, particularly based on type and size. In this work, we combine a model-based supervised learning algorithm with a wide-field common-path interferometric microscopy method to achieve accurate nanoparticle classification. We verify our classification schemes experimentally by blindly detecting gold and polystyrene nanospheres, and then classifying them in terms of type and size.en_US
dc.description.sponsorshipO. A. gratefully acknowledges support from I/UCRC Center for Biophotonic Sensors and Systems (CBSS). (I/UCRC Center for Biophotonic Sensors and Systems (CBSS))en_US
dc.format.extentp. 4238 - 4242en_US
dc.languageEnglish
dc.language.isoen_US
dc.publisherOPTICAL SOC AMERen_US
dc.relation.ispartofAPPLIED OPTICS
dc.rights"Copyright 2017 Optical Society of America. The final author draft of this article is being made available in OpenBU under Boston University's open access.policy."en_US
dc.subjectScience & technologyen_US
dc.subjectPhysical sciencesen_US
dc.subjectOpticsen_US
dc.subjectSupport vector machinesen_US
dc.subjectComplex mediaen_US
dc.subjectOptical physicsen_US
dc.subjectMechanical engineeringen_US
dc.subjectElectrical and electronic engineeringen_US
dc.titleNanoparticle classification in wide-field interferometric microscopy by supervised learning from modelen_US
dc.typeArticleen_US
dc.description.versionPublished versionen_US
dc.identifier.doi10.1364/AO.56.004238
pubs.elements-sourceweb-of-scienceen_US
pubs.notesEmbargo: Not knownen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Engineeringen_US
pubs.organisational-groupBoston University, College of Engineering, Department of Electrical & Computer Engineeringen_US
pubs.publication-statusPublisheden_US
dc.identifier.orcid0000-0002-8594-892X (Unlu, M Selim)
dc.identifier.mycv186576


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