A novel artificial intelligence-powered tool for automated root canal segmentation in single-rooted teeth on cone-beam computed tomography.

Journal: International endodontic journal
PMID: 39873266

Abstract

AIM: To develop and validate an artificial intelligence (AI)-powered tool based on convolutional neural network (CNN) for automatic segmentation of root canals in single-rooted teeth using cone-beam computed tomography (CBCT).

Authors

  • Airton Oliveira Santos-Junior
    Department of Restorative Dentistry, School of Dentistry, São Paulo State University (UNESP), Araraquara, São Paulo, Brazil.
  • Rocharles Cavalcante Fontenele
    OMFS IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, University of Leuven and Department of Oral & Maxillofacial Surgery, University Hospitals Leuven, KU Leuven, Kapucijnenvoer 7, 3000, Leuven, Belgium; Department of Oral Diagnosis, Piracicaba Dental School, University of Campinas, Piracicaba, Sao Paulo, Brazil.
  • Frederico Sampaio Neves
    OMFS IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, University of Leuven, Leuven, Belgium.
  • Mário Tanomaru-Filho
    Department of Restorative Dentistry, Dental School, São Paulo State University (UNESP), Araraquara, SP, Brazil.
  • Reinhilde Jacobs
    OMFS IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, University of Leuven and Department of Oral & Maxillofacial Surgery, University Hospitals Leuven, KU Leuven, Kapucijnenvoer 7, 3000, Leuven, Belgium; Department of Dental Medicine, Karolinska Institutet, Stockholm, Sweden. Electronic address: reinhilde.jacobs@ki.se.

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