Colonic polyp detection in CT colonography with fuzzy rule based 3D template matching

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dc.contributor.authorKılıç, Niyazi
dc.contributor.authorUçan, Osman N.
dc.contributor.authorOsman, Onur
dc.date.accessioned2020-11-21T15:53:21Z
dc.date.available2020-11-21T15:53:21Z
dc.date.issued2009en_US
dc.departmentİstanbul Ticaret Üniversitesien_US
dc.descriptionPubMed ID: 19238892en_US
dc.description.abstractIn this paper, we introduced a computer aided detection (CAD) system to facilitate colonic polyp detection in computer tomography (CT) data using cellular neural network, genetic algorithm and three dimensional (3D) template matching with fuzzy rule based tresholding. The CAD system extracts colon region from CT images using cellular neural network (CNN) having A, B and I templates that are optimized by genetic algorithm in order to improve the segmentation performance. Then, the system performs a 3D template matching within four layers with three different cell of 8×8, 12×12 and 20×20 to detect polyps. The CAD system is evaluated with 1043 CT colonography images from 16 patients containing 15 marked polyps. All colon regions are segmented properly. The overall sensitivity of proposed CAD system is 100% with the level of 0.53 false positives (FPs) per slice and 11.75 FPs per patient for the 8×8 cell template. For the 12×12 cell templates, detection sensitivity is 100% at 0.494 FPs per slice and 8.75 FPs per patient and for the 20×20 cell templates, detection sensitivity is 86.66% with the level of 0.452 FPs per slice and 6.25 FPs per patient. © 2008 Springer Science+Business Media, LLC.en_US
dc.description.sponsorshipIstanbul Üniversitesi -- Acknowledgement This research is supported by Istanbul University, Research Fund. Project No: T-502 and YÖP-19/07122005. -- --en_US
dc.identifier.doi10.1007/s10916-008-9159-3en_US
dc.identifier.endpage18en_US
dc.identifier.issn0148-5598
dc.identifier.issue1en_US
dc.identifier.pmid19238892en_US
dc.identifier.scopus2-s2.0-58349111309en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage9en_US
dc.identifier.urihttps://doi.org/10.1007/s10916-008-9159-3
dc.identifier.urihttps://hdl.handle.net/11467/3556
dc.identifier.volume33en_US
dc.identifier.wosWOS:000262482900002en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Medical Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCellular neural networksen_US
dc.subjectColon segmentationen_US
dc.subjectColonic polyp detectionen_US
dc.subjectCT colonographyen_US
dc.subjectFuzzy logicen_US
dc.subjectGenetic algorithmen_US
dc.titleColonic polyp detection in CT colonography with fuzzy rule based 3D template matchingen_US
dc.typeArticleen_US

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