Automated cell nucleus detection for large-volume electron microscopy of neural tissue

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dc.authorid0000-0002-8649-6013
dc.contributor.authorTek, Faik Borayen_US
dc.contributor.authorKroeger, Thorbenen_US
dc.contributor.authorHamprecht, Fred A.en_US
dc.contributor.authorMikula, Shawnen_US
dc.date.accessioned2019-06-27T18:56:20Z
dc.date.available2019-06-27T18:56:20Z
dc.date.issued2014-04-29
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Computer Engineeringen_US
dc.description.abstractVolumetric electron microscopy techniques, such as serial block-face electron microscopy (SBEM), generate massive amounts of image data that are used for reconstructing neural circuits. Typically, this requires time-intensive manual annotation of cells and their connections. To facilitate this analysis, we study the problem of automated detection of cell nuclei in a new SBEM dataset that contains cerebral cortex, white matter, and striatum from an adult mouse brain. The dataset was manually annotated to identify the locations of all 3309 cell nuclei in the volume. We make both dataset and annotations available here. Using a hybrid approach that combines interactive learning, morphological processing, and object level feature classification, we demonstrate automated detection of cell nuclei at 92.4% recall and 95.1% precision. These algorithms are not RAM-limited and can scale to arbitrarily large datasets.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationTek, F. B., Kroeger, T., Mikula, S. & Hamprecht, F. A. (2014). Automated cell nucleus detection for large-volume electron microscopy of neural tissue. Paper presented at the 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), 69-72. doi:10.1109/ISBI.2014.6867811en_US
dc.identifier.endpage72
dc.identifier.isbn9781467319614
dc.identifier.issn1945-7928
dc.identifier.scopus2-s2.0-84927539855
dc.identifier.scopusqualityN/A
dc.identifier.startpage69
dc.identifier.urihttps://hdl.handle.net/11729/1637
dc.identifier.urihttp://dx.doi.org/10.1109/ISBI.2014.6867811
dc.identifier.wosWOS:000392750900018
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakConference Proceedings Citation Index – Science (CPCI-S)en_US
dc.institutionauthorTek, Faik Borayen_US
dc.institutionauthorid0000-0002-8649-6013
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherIEEEen_US
dc.relation.ispartof2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAutomated nucleus detectionen_US
dc.subjectBlock-face electron microscopyen_US
dc.subjectInteractive segmentationen_US
dc.subjectRandom foresten_US
dc.subjectBlock-wise connecteden_US
dc.subjectComponentsen_US
dc.subjectConnectomicsen_US
dc.subjectSomaen_US
dc.subjectIdentificationen_US
dc.subjectBrainen_US
dc.titleAutomated cell nucleus detection for large-volume electron microscopy of neural tissueen_US
dc.typeConference Objecten_US

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