Automated permanent tooth detection and numbering on panoramic radiograph using a deep learning approach.

Journal: Oral surgery, oral medicine, oral pathology and oral radiology

PMID: 37633788

OBJECTIVE: This study aimed to assess the performance of the deep learning (DL) model for automated tooth numbering in panoramic radiographs.

Ramadhan Hardani Putra

Department of Dentomaxillofacial Radiology, Faculty of Dental Medicine, Universitas Airlangga, Surabaya, Indonesia.
Eha Renwi Astuti

Department of Dentomaxillofacial Radiology, Faculty of Dental Medicine, Universitas Airlangga, Surabaya, Indonesia. Electronic address: eha-r-a@fkg.unair.ac.id.
Dina Karimah Putri

Department of Dentomaxillofacial Radiology, Faculty of Dental Medicine, Universitas Airlangga, Surabaya, Indonesia; Division of Dental Informatics and Radiology, Tohoku University Graduate School of Dentistry, Sendai, Japan.
Monica Widiasri

Department of Informatics, Faculty of Engineering, Universitas Surabaya, Surabaya, Indonesia; Department of Informatics, Faculty of Intelligent Electrical and Informatics Technology, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia.
Putri Alfa Meirani Laksanti

Undergraduate Study Program, Faculty of Dental Medicine, Universitas Airlangga, Surabaya, Indonesia.
Hilda Majidah

Undergraduate Study Program, Faculty of Dental Medicine, Universitas Airlangga, Surabaya, Indonesia.
Nobuhiro Yoda

Division of Advanced Prosthetic Dentistry, Tohoku University, Graduate School of Dentistry, Sendai, Japan.

Deep Learning Dentition, Permanent Humans Male Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted Radiography, Panoramic Software Tooth

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