A robust deep learning model for the classification of dental implant brands.

Journal: Journal of stomatology, oral and maxillofacial surgery
PMID: 38462066

Abstract

OBJECTIVE: In cases where the brands of implants are not known, treatment options can be significantly limited in potential complications arising from implant procedures. This research aims to explore the application of deep learning techniques for the classification of dental implant systems using panoramic radiographs. The primary objective is to assess the superiority of the proposed model in achieving accurate and efficient dental implant classification.

Authors

  • Ikbal Leblebicioglu Kurtulus
    Department of Prosthodontics, Faculty of Dentistry, Erciyes University, Kayseri, Turkey.
  • Mohammed Lubbad
    Department of Computer Engineering, Faculty of Engineering, Erciyes University, Kayseri, Turkey.
  • Ozden Melis Durmaz Yilmaz
    Department of Prosthodontics, Faculty of Dentistry, Erciyes University, Kayseri, Turkey. Electronic address: ozdenmelisdurmaz47@gmail.com.
  • Kerem Kilic
    Department of Prosthodontics, Faculty of Dentistry, Erciyes University, Kayseri, Turkey.
  • Dervis Karaboga
    Computer Engineering Department, Engineering Faculty, Erciyes University, Kayseri, Turkey; Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia.
  • Alper Basturk
    Computer Engineering Department, Engineering Faculty, Erciyes University, Kayseri, Turkey.
  • Bahriye Akay
    Computer Engineering Department, Engineering Faculty, Erciyes University, Kayseri, Turkey.
  • Ufuk Nalbantoglu
    Computer Engineering Department, Engineering Faculty, Erciyes University, Kayseri, Turkey.
  • Serkan Yilmaz
    Faculty of Dentistry, Department of Oral and Maxillofacial Radiology, Erciyes University, Kayseri, Turkey.
  • Mustafa Ayata
    Private Practice, Ortoperio Oral and Dental Health Polyclinic, Kayseri, Türkiye. dt.mustafaayata@gmail.com.
  • Ishak Pacal
    Computer Engineering Department, Engineering Faculty, Igdir University, Igdir, Turkey. Electronic address: ishak.pacal@igdir.edu.tr.

Keywords

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