Panoramik Görüntülerde Diş Numaralandırma: Derin Öğrenme ve Sezgisel Algoritmaya Dayalı Yeni Bir Yöntem / Numbering Teeth in Panoramic Images: A Novel Method Based On Deep Learning And Heuristic Algorithm
Yazarlar (4)
Dr. Öğr. Üyesi Ahmet KARAOĞLU Sinop Üniversitesi, Türkiye
Caner Özcan Karabük Üniversitesi, Türkiye
Adem Pekince Karabük Üniversitesi, Türkiye
Prof. Dr. Yasin Yaşa Ordu Üniversitesi, Türkiye
Makale Türü Açık Erişim Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
Dergi Adı Engineering Science and Technology an International Journal (Q1)
Dergi ISSN 2215-0986 Dergi Bilgileri (2023)
Dergi Tarandığı Indeksler SCI-Expanded
Makale Dili İngilizce Basım Tarihi 01-2023
Cilt / Sayı / Sayfa 37 / 1 / 101316–0 DOI 10.1016/j.jestch.2022.101316
Makale Linki http://dx.doi.org/10.1016/j.jestch.2022.101316
UAK Araştırma Alanları
Yapay Zeka
Özet
Dental problems are one of the most common health problems for people. To detect and analyze these problems, dentists often use panoramic radiographs that show the entire mouth and have low radiation exposure and exposure time. Analyzing these radiographs is a lengthy and tedious process. Recent studies have ensured dental radiologists can perform the analyses faster with various artificial intelligence supports. In this study, the numbering performance of Mask R-CNN and our heuristic algorithm-based method was verified on panoramic dental radiographs according to the Federation Dentaire Internationale (FDI) system. Ground-truth labelling of images required for training the deep learning algorithm was performed by two dental radiologists using the web-based labelling software DentiAssist created by the first author. The dataset was created from 2702 anonymized panoramic radiographs. The dataset …
Anahtar Kelimeler
Deep learning | Heuristic algorithm | Mask R-CNN | Numbering | Panoramic radiographs | Segmentation