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Nodule detection in a lung region that's segmented with using genetic cellular neural networks and 3D template matching with fuzzy rule based thresholding

dc.contributor.authorOsman, Onur
dc.contributor.authorUcan, Osman N.
dc.contributor.authorOzekes, Serhat
dc.date.accessioned2021-03-03T17:09:49Z
dc.date.available2021-03-03T17:09:49Z
dc.date.issued2008
dc.identifier.citationOzekes S., Osman O., Ucan O. N. , "Nodule detection in a lung region that's segmented with using genetic cellular neural networks and 3D template matching with fuzzy rule based thresholding", KOREAN JOURNAL OF RADIOLOGY, cilt.9, sa.1, ss.1-9, 2008
dc.identifier.issn1229-6929
dc.identifier.othervv_1032021
dc.identifier.otherav_48591a09-fbc1-40dd-ba2c-21060f3b2880
dc.identifier.urihttp://hdl.handle.net/20.500.12627/52129
dc.identifier.urihttps://doi.org/10.3348/kjr.2008.9.1.1
dc.description.abstractObjective: The purpose of this study was to develop a new method for automated lung nodule detection in serial section CT images with using the characteristics of the 3D appearance of the nodules that distinguish themselves from the vessels.
dc.language.isoeng
dc.subjectNükleer Tıp
dc.subjectRADYOLOJİ, NÜKLEER TIP ve MEDİKAL GÖRÜNTÜLEME
dc.subjectKlinik Tıp
dc.subjectKlinik Tıp (MED)
dc.subjectTıp
dc.subjectSağlık Bilimleri
dc.subjectDahili Tıp Bilimleri
dc.titleNodule detection in a lung region that's segmented with using genetic cellular neural networks and 3D template matching with fuzzy rule based thresholding
dc.typeMakale
dc.relation.journalKOREAN JOURNAL OF RADIOLOGY
dc.contributor.departmentİstanbul Ticaret Üniversitesi , ,
dc.identifier.volume9
dc.identifier.issue1
dc.identifier.startpage1
dc.identifier.endpage9
dc.contributor.firstauthorID185971


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