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dc.contributor.authorKilic, Niyazi
dc.contributor.authorUcan, Osman Nuri
dc.contributor.authorOsman, Onur
dc.date.accessioned2021-03-04T10:20:36Z
dc.date.available2021-03-04T10:20:36Z
dc.identifier.citationKilic N., Osman O., Ucan O. N. , "Colon Segmentation and The Detection of Colonic Polyp with Template Matching in CT Images", IEEE 16th Signal Processing and Communications Applications Conference, Aydın, Türkiye, 20 - 22 Nisan 2008, ss.784-785
dc.identifier.othervv_1032021
dc.identifier.otherav_6cb250a5-8b09-4051-82be-ed6687e624b3
dc.identifier.urihttp://hdl.handle.net/20.500.12627/75131
dc.identifier.urihttps://doi.org/10.1109/siu.2008.4632731
dc.description.abstractIn this paper, we introduced a novel Computer Aided Detection (CAD) system for colonic polyp defection in CT data. The CAD system extracts colon region from CT images using cellular neural network (CNN) which its parameters of A,B and I templates are optimized by genetic algorithm in order to improve segmentation performance. Region of interest (ROI) of all slices were combined together to acquire a 3D ROI image and then we generate a 3D ROI image (3D segmented colon. Then the system performs 3D template matching with jour layers of 12 x 12 cells to detect polyps. The CAD system was evaluated with 1148 CT images from 11 patients containing 15 marked polyps. The overall sensitivity of our CAD system is, 100% with the level of 10 FPs per case
dc.language.isoeng
dc.subjectBilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği
dc.subjectSinyal İşleme
dc.subjectMühendislik ve Teknoloji
dc.subjectKlinik Tıp (MED)
dc.subjectTELEKOMÜNİKASYON
dc.subjectTıp
dc.subjectSağlık Bilimleri
dc.subjectGÖRÜNTÜLEME BİLİMİ VE FOTOĞRAF TEKNOLOJİSİ
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectMühendislik
dc.subjectMÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK
dc.subjectKlinik Tıp
dc.titleColon Segmentation and The Detection of Colonic Polyp with Template Matching in CT Images
dc.typeBildiri
dc.contributor.departmentİstanbul Ticaret Üniversitesi , ,
dc.contributor.firstauthorID134579


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