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dc.contributor.authorWilliamson, David Roddan
dc.contributor.authorNordtug, Trond
dc.contributor.authorLeirvik, Frode
dc.contributor.authorKvæstad, Bjarne
dc.contributor.authorHansen, Bjørn Henrik
dc.contributor.authorLudvigsen, Martin
dc.contributor.authorDavies, Emlyn John
dc.date.accessioned2022-10-31T14:11:27Z
dc.date.available2022-10-31T14:11:27Z
dc.date.created2022-09-29T08:55:07Z
dc.date.issued2022
dc.identifier.citationMethodsX. 2022, 9, 101773, 1-15.en_US
dc.identifier.issn2215-0161
dc.identifier.urihttps://hdl.handle.net/11250/3029184
dc.description.abstractMicroscopic imaging and morphometric measurement of fish embryos and larvae is essential in environmental monitoring of fish populations and to evaluate larvae development in aquaculture. Traditional microscopy methods require time-consuming, repetitive work by human experts. We present a method for fast imaging and analysis of millimetre-scale ichthyoplankton suspended in seawater. Our system can be easily built from common and off-the-shelf components and uses open-source software for image capture and analysis. Our system obtains images of similar quality to traditional microscopy, and biological measurements comparable to those by human experts, with minimal human interaction. This saves time and effort, while increasing the size of data sets obtained. We demonstrate our approach with cod eggs and larvae, and present results showing biologically relevant endpoints including egg diameter, larval standard length, yolk volume and eye diameter, with comparison to similar measurements reported in the literature. • High throughput, microscope-scale imaging of fish eggs and larvae • Automated measurement of biologically relevant endpoints • Easily built from off-the-shelf components and open-source softwareen_US
dc.language.isoengen_US
dc.publisherElseiveren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.subjectAtlantic coden_US
dc.subjectAutomated biometryen_US
dc.subjectMachine learningen_US
dc.subjectComputer visionen_US
dc.subjectFlow cytometryen_US
dc.subjectMicroscopyen_US
dc.titleA flow-through imaging system for automated measurement of ichthyoplanktonen_US
dc.title.alternativeA flow-through imaging system for automated measurement of ichthyoplanktonen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2022 The Author(s). Published by Elsevier B.Ven_US
dc.source.pagenumber15en_US
dc.source.volume9en_US
dc.source.journalMethodsXen_US
dc.identifier.doi10.1016/j.mex.2022.101773
dc.identifier.cristin2056660
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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