AUTOMATIC COLON SEGMENTATION USING CELLULAR NEURAL NETWORK FOR THE DETECTION OF COLORECTAL POLYPS

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dc.authoridosman, onur/0000-0001-7675-7999
dc.contributor.authorKilic, Niyazi
dc.contributor.authorOsman, Onur
dc.contributor.authorUcan, Osman N.
dc.contributor.authorDemirel, Kemal
dc.date.accessioned2024-10-12T19:43:07Z
dc.date.available2024-10-12T19:43:07Z
dc.date.issued2007
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.endpage+en_US
dc.identifier.issn1303-0914
dc.identifier.issue2en_US
dc.identifier.startpage419en_US
dc.identifier.urihttps://hdl.handle.net/11467/8770
dc.identifier.volume7en_US
dc.identifier.wosWOS:000409729900006en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherIstanbul Univ, Fac Engineeringen_US
dc.relation.ispartofIstanbul University-Journal Of Electrical And Electronics Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzWoS_2024en_US
dc.subjectVirtual colonoscopyen_US
dc.subjectSegmentationen_US
dc.subjectColorectal polypen_US
dc.subjectCellular Neural Networken_US
dc.titleAUTOMATIC COLON SEGMENTATION USING CELLULAR NEURAL NETWORK FOR THE DETECTION OF COLORECTAL POLYPSen_US
dc.typeArticleen_US

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