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Two-step deep learning models for detection and identification of the manufacturers and types of dental implants on panoramic radiographs.
Ariji, Yoshiko; Kusano, Kaoru; Fukuda, Motoki; Wakata, Yo; Nozawa, Michihito; Kotaki, Shinya; Ariji, Eiichiro; Baba, Shunsuke.
Afiliación
  • Ariji Y; Department of Oral Radiology, Osaka Dental University, 1-5-17, Otemae, Chuo-ku, Osaka, 540-0008, Japan. ariji-y@cc.osaka-dent.ac.jp.
  • Kusano K; Department of Oral Implantology, Osaka Dental University, Osaka, Japan.
  • Fukuda M; Department of Oral Radiology, Osaka Dental University, 1-5-17, Otemae, Chuo-ku, Osaka, 540-0008, Japan.
  • Wakata Y; Department of Oral Implantology, Osaka Dental University, Osaka, Japan.
  • Nozawa M; Department of Oral Radiology, Osaka Dental University, 1-5-17, Otemae, Chuo-ku, Osaka, 540-0008, Japan.
  • Kotaki S; Department of Oral Radiology, Osaka Dental University, 1-5-17, Otemae, Chuo-ku, Osaka, 540-0008, Japan.
  • Ariji E; Department of Oral and Maxillofacial Radiology, Aichi-Gakuin University, Nagoya, Japan.
  • Baba S; Department of Oral Implantology, Osaka Dental University, Osaka, Japan.
Odontology ; 2024 Aug 29.
Article en En | MEDLINE | ID: mdl-39198339
ABSTRACT
The purpose of this study is to develop two-step deep learning models that can automatically detect implant regions on panoramic radiographs and identify several types of implants. A total of 1,574 panoramic radiographs containing 3675 implants were included. The implant manufacturers were Kyocera, Dentsply Sirona, Straumann, and Nobel Biocare. Model A was created to detect oral implants and identify the manufacturers using You Only Look Once (YOLO) v7. After preparing the image patches that cropped the implant regions detected by model A, model B was created to identify the implant types per manufacturer using EfficientNet. Model A achieved very high performance, with recall of 1.000, precision of 0.979, and F1 score of 0.989. It also had accuracy, recall, precision, and F1 score of 0.98 or higher for the classification of the manufacturers. Model B had high classification metrics above 0.92, exception for Nobel's class 2 (Parallel). In this study, two-step deep learning models were built to detect implant regions, identify four manufacturers, and identify implant types per manufacturer.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Odontology Asunto de la revista: ODONTOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Japón
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Odontology Asunto de la revista: ODONTOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Japón