Accuracy of artificial intelligence-based segmentation of the mandibular canal in CBCT.

Journal: Clinical oral implants research
PMID: 38845570

Abstract

OBJECTIVES: To investigate the accuracy of artificial intelligence (AI)-based segmentation of the mandibular canal, compared to the conventional manual tracing, implementing implant planning software.

Authors

  • Panagiotis Ntovas
    Department of Prosthodontics, School of Dental Medicine, Tufts University School of Dental Medicine, Boston, Massachusetts, USA.
  • Laurent Marchand
    Department of Prosthodontics, School of Dental Medicine, Tufts University School of Dental Medicine, Boston, Massachusetts, USA.
  • Matthew Finkelman
    Department of Public Health and Community Service, Tufts University School of Dental Medicine, Boston, MA, USA.
  • Marta Revilla-León
    Affiliate Assistant Professor, Graduate Prosthodontics, Department of Restorative Dentistry, School of Dentistry, University of Washington, Seattle, Wash and Faculty and Director of Research and Digital Dentistry, Kois Center, Seattle, Wash; Adjunct Professor, Department of Prosthodontics, School of Dental Medicine, Tufts University, Boston, MA.
  • Wael Att

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