Automatic colon segmentation using cellular neural network for colorectal polyps detection

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dc.contributor.authorKılıç, Niyazi
dc.contributor.authorOsman, Onur
dc.contributor.authorUçan, Osman N.
dc.contributor.authorDemirel, Kemal
dc.date.accessioned2020-11-21T15:55:17Z
dc.date.available2020-11-21T15:55:17Z
dc.date.issued2007en_US
dc.departmentİstanbul Ticaret Üniversitesien_US
dc.description.abstractIn this paper, an automatic colon segmentation method for Computed Tomography (CT) colonography is presented. Colon segmentation is considered in order to prevent the time consumption while searching polyps out of the colon region and reduce radiologists’ interpretation time. The proposed method is the combination of pre-processing and Cellular Neural Networks (CNN). Also recurrent perceptron learning algorithm (RPLA) is used for CNN training. Original CT images are passed through a threshold and then CNN is used to erase unrelated small objects and smooth sharp corners. It is expected automatic colon segmentation will improve the radiologists’ diagnostic performance.en_US
dc.identifier.endpage422en_US
dc.identifier.issn1303-0914
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-46649111333en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage419en_US
dc.identifier.trdizinid114056en_US
dc.identifier.urihttps://app.trdizin.gov.tr/makale/TVRFME1EVTJOZz09
dc.identifier.urihttps://hdl.handle.net/11467/3973
dc.identifier.volume7en_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.ispartofIstanbul University Journal of Electrical and Electronics Engineeringen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMühendisliken_US
dc.subjectElektrik ve Elektroniken_US
dc.titleAutomatic colon segmentation using cellular neural network for colorectal polyps detectionen_US
dc.typeArticleen_US

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