Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/91402
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dc.contributor.authorErlend, Hodnelanden
dc.contributor.authorNickolay V., Bukoreshtlieven
dc.contributor.authorTilo W., Eichleren
dc.contributor.authorTai, Xue Chengen
dc.contributor.authorSteffen, Gurkeen
dc.contributor.authorArvid, Lundervolden
dc.contributor.authorHans-Hermann, Gerdesen
dc.date.accessioned2009-08-12T03:09:32Zen
dc.date.accessioned2019-12-06T18:05:02Z-
dc.date.available2009-08-12T03:09:32Zen
dc.date.available2019-12-06T18:05:02Z-
dc.date.copyright2009en
dc.date.issued2009en
dc.identifier.citationHodneland, E., Bukoreshtliev, N. V., Eichler, T. W., Tai, X. C., Gurke, S., Lundervold, A., et al.(2009). A unified framework for automated 3D whole cell segmentation of living cells and a comprehensive segmentation evaluation. IEEE Transactions on Medical Imaging, 28(5), 720-738.en
dc.identifier.issn0278-0062en
dc.identifier.urihttps://hdl.handle.net/10356/91402-
dc.identifier.urihttp://hdl.handle.net/10220/6055en
dc.description.abstractThis work presents a unified framework for whole cell segmentation of surface stained living cells from 3-D data sets of fluorescent images. Every step of the process is described, image acquisition, prefiltering, ridge enhancement, cell segmentation, and a segmentation evaluation. The segmentation results from two different automated approaches for segmentation are compared to manual segmentation of the same data using a rigorous evaluation scheme. This revealed that combination of the respective cell types with the most suitable microscopy method resulted in high success rates up to 97%. The described approach permits to automatically perform a statistical analysis of various parameters from living cells.en
dc.format.extent19 p.en
dc.language.isoenen
dc.relation.ispartofseriesIEEE Transactions on Medical Imaging.en
dc.rightsIEEE Transactions on Medical Imaging © copyright 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. http://www.ieee.org/portal/site.en
dc.subjectDRNTU::Science::Mathematics::Applied mathematicsen
dc.subjectDRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer visionen
dc.titleA unified framework for automated 3D whole cell segmentation of living cells and a comprehensive segmentationen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Physical and Mathematical Sciencesen
dc.identifier.openurlhttp://sfxna09.hosted.exlibrisgroup.com:3410/ntu/sfxlcl3?sid=metalib:EBSCO_APH&id=doi:&genre=&isbn=&issn=02780062&date=2009&volume=28&issue=5&spage=720&epage=738&aulast=Hodneland&aufirst=%20Erlend&auinit=&title=IEEE%20Transactions%20on%20Medical%20Imaging&atitle=A%20Unified%20Framework%20for%20Automated%203%2DD%20Segmentation%20of%20Surface%2DStained%20Living%20Cells%20and%20a%20Comprehensive%20Segmentation%20Evaluation%2E&sicien
dc.identifier.doi10.1109/TMI.2008.2011522en
dc.description.versionPublished versionen
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