Metaphase finding with deep convolutional neural networks

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dc.contributor.authorMoazzen, Yaser
dc.contributor.authorCapar, Abdulkerim
dc.contributor.authorAlbayrak, Abdulkadir
dc.contributor.authorCalik, Nurullah
dc.contributor.authorToreyin, Behcet Ugur
dc.date.accessioned2024-04-24T16:10:58Z
dc.date.available2024-04-24T16:10:58Z
dc.date.issued2019
dc.departmentDicle Üniversitesien_US
dc.description.abstractBackground: Finding analyzable metaphase chromosome images is an essential step in karyotyping which is a common task for clinicians to diagnose cancers and genetic disorders precisely. This step is tedious and time-consuming. Hence developing automated fast and reliable methods to assist clinical technicians becomes indispensable. Previous approaches include methods with feature extraction followed by rule or quality based classifiers, component analysis, and neural networks. Methods: A two-stage automated metaphase-finding scheme, consisting of an image processing based metaphase detection stage, and a deep convolutional neural network based selection stage is proposed. The first stage detects metaphase images from 10x scan of specimen slides. The selection stage, on the other hand, selects the analyzable ones among them. Results: The proposed scheme has a 99.33% true positive rate and 0.34% of the false positive rate of metaphase finding. Conclusion: This study demonstrates an effective scheme for the automated finding of analyzable metaphase images with high True positive and low False positive rates. (C) 2019 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.bspc.2019.04.017
dc.identifier.endpage361en_US
dc.identifier.issn1746-8094
dc.identifier.issn1746-8108
dc.identifier.scopus2-s2.0-85065863389en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage353en_US
dc.identifier.urihttps://doi.org/10.1016/j.bspc.2019.04.017
dc.identifier.urihttps://hdl.handle.net/11468/15206
dc.identifier.volume52en_US
dc.identifier.wosWOS:000473381100037
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofBiomedical Signal Processing and Controlen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMetaphase Detectionen_US
dc.subjectKaryotypingen_US
dc.subjectDeep Convolutional Neural Networksen_US
dc.titleMetaphase finding with deep convolutional neural networksen_US
dc.typeArticleen_US

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