Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7443
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dc.contributor.authorGüven, Ali-
dc.contributor.authorYetik, İmam Şamil-
dc.contributor.authorÇulhaoğlu, Ahmet-
dc.contributor.authorOrhan, Kaan-
dc.contributor.authorKılıçarslan, Mehmet Kılıçarslan-
dc.date.accessioned2021-09-11T15:57:03Z-
dc.date.available2021-09-11T15:57:03Z-
dc.date.issued2020en_US
dc.identifier.citation28th Signal Processing and Communications Applications Conference (SIU) -- OCT 05-07, 2020 -- ELECTR NETWORKen_US
dc.identifier.isbn978-1-7281-7206-4-
dc.identifier.issn2165-0608-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/7443-
dc.description.abstractSegmentation of teeth region from the dental panoramic X-Ray images is an important task in determining various diseases. The main goal of this article is to be able to automatically segment the region of teeth in panoramic x-ray images. First, the center point of the teeth area in the images was determined automatically. Then, a feature set was developed including intensity values of pixels, x-coordinate relative to this center point, y-coordinate relative to this point, and the pixel values obtained by subtraction of maximum and minimum values in 3x3 window. CatBoost algorithm was used for machine learning. When creating the machine learning model, k-fold cross validation of training data set and grid search optimization of hyper parameters, were applied to avoid over fitting of data set. The results were analyzed using the learning curve, F1, accuracy, recall, and precision scores.en_US
dc.description.sponsorshipIstanbul Medipol Univen_US
dc.language.isotren_US
dc.publisherIEEEen_US
dc.relation.ispartof2020 28Th Signal Processing And Communications Applications Conference (Siu)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectdental panoramic X-Ray imagesen_US
dc.subjectmachine learningen_US
dc.subjectimage processingen_US
dc.subjectimage segmentationen_US
dc.subjectteeth segmentationen_US
dc.titleSegmentation of Teeth Region Via Machine Learning in Panoramic X-Ray Dental Imagesen_US
dc.typeConference Objecten_US
dc.relation.ispartofseriesSignal Processing and Communications Applications Conferenceen_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümütr_TR
dc.identifier.wosWOS:000653136100492en_US
dc.identifier.scopus2-s2.0-85100287745en_US
dc.institutionauthorYetik, Imam Şamil-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conference28th Signal Processing and Communications Applications Conference (SIU)en_US
item.openairetypeConference Object-
item.languageiso639-1tr-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.5. Department of Electrical and Electronics Engineering-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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