A deep learning approach for dental implant planning in cone-beam computed tomography images.

Journal: BMC medical imaging
PMID: 34011314

Abstract

BACKGROUND: The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images.

Authors

  • Sevda Kurt Bayrakdar
    Department of Periodontology, Faculty of Dentistry, Eskisehir Osmangazi University, Eskişehir, Turkey.
  • Kaan Orhan
    Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Dentomaxillofacial Radiologist, Ankara University, Ankara, Turkey.
  • İbrahim Şevki Bayrakdar
    Department of Oral Diagnosis and Radiology, Faculty of Dentistry, Eskişehir Osmangazi University, Eskişehir, Turkey.
  • Elif Bilgir
    Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Eskisehir Osmangazi University, Eskisehir, Turkey.
  • Matvey Ezhov
    Diagnocat, Inc, San Francisco, USA.
  • Maxim Gusarev
    Diagnocat, Inc, San Francisco, USA.
  • Eugene Shumilov
    Diagnocat, Inc, San Francisco, USA.

Keywords

External Resources

Popular Topics
Recent Journals