Artificial intelligence system for automatic deciduous tooth detection and numbering in panoramic radiographs.

Kılıc, Münevver; Bayrakdar, Ibrahim; Çelik, Özer; Bilgir, Elif; Orhan, Kaan; Aydın, Ozan; Kaplan, Fatma; Sağlam, Hande; Odabaş, Alper; Aslan, Ahmet; Yılmaz, Ahmet

doi:10.1259/dmfr.20200172

Artificial intelligence system for automatic deciduous tooth detection and numbering in panoramic radiographs.

Kılıc M., Bayrakdar I. S., Çelik Ö., Bilgir E., Orhan K., Aydın O. B., ...Daha Fazla

Dento maxillo facial radiology, cilt.50, ss.20200172, 2021 (SCI-Expanded, Scopus)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 50
Basım Tarihi: 2021
Doi Numarası: 10.1259/dmfr.20200172
Dergi Adı: Dento maxillo facial radiology
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, MEDLINE
Sayfa Sayıları: ss.20200172
Anahtar Kelimeler: Artificial intelligence, deep learning, tooth detecting, panoramic radiography, children, pediatric dentistry, deciduous tooth, CONVOLUTIONAL NEURAL-NETWORK, TEETH, CLASSIFICATION, DIAGNOSIS, FUTURE
Atatürk Üniversitesi Adresli: Evet

Özet

Objective: This study evaluated the use of a deep-learning approach for automated detection and numbering of deciduous teeth in children as depicted on panoramic radiographs.