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dc.contributor.authorSchulz, Jörn
dc.contributor.authorSkrøvseth, Stein Olav
dc.contributor.authorTømmerås, Veronika Kristine
dc.contributor.authorMarienhagen, Kirsten
dc.contributor.authorGodtliebsen, Fred
dc.date.accessioned2015-03-13T08:27:23Z
dc.date.available2015-03-13T08:27:23Z
dc.date.issued2014-01-25
dc.descriptionA manuscript version of this article is part of Jörn Schulz' doctoral thesis, which is available in Munin at <a href=http://hdl.handle.net/10037/5869>http://hdl.handle.net/10037/5869</a>en
dc.identifier.citationBMC Medical Imaging 2014, 14:4en_US
dc.identifier.cristinIDFRIDAID 1100086
dc.identifier.doiDOI: 10.1186/1471-2342-14-4
dc.identifier.issn1471-2342
dc.identifier.urihttps://hdl.handle.net/10037/7473
dc.identifier.urnURN:NBN:no-uit_munin_7084
dc.language.isoengen_US
dc.publisherBioMed Centralen_US
dc.rights.accessRightsopenAccess
dc.subjectVDP::412en_US
dc.subjectVDP::762en_US
dc.subjectDelineationen_US
dc.subjectEllipse modelen_US
dc.subjectEmpirical Bayesen_US
dc.subjectProstateen_US
dc.subjectRadiotherapy treatment planningen_US
dc.subjectStatistical shape analysisen_US
dc.titleA semiautomatic tool for prostate segmentation in radiotherapy treatment planningen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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