Deep learning for the identification of ridge deficiency around dental implants.

Journal: Clinical implant dentistry and related research
PMID: 38151900

Abstract

OBJECTIVES: This study aimed to use a deep learning (DL) approach for the automatic identification of the ridge deficiency around dental implants based on an image slice from cone-beam computerized tomography (CBCT).

Authors

  • Cheng-Hung Lin
    Department of Electrical Engineering and Biomedical Engineering Research Center, Yuan Ze University, Jungli 32003, Taiwan.
  • Hom-Lay Wang
    Department of Periodontics and Oral Medicine, the University of Michigan School of Dentistry, Ann Arbor, MI 48109.
  • Li-Wen Yu
    Graduate Institute of Clinical Dentistry, School of Dentistry, College of Medicine, National Taiwan University, Taipei, Taiwan.
  • Po-Yung Chou
    Department of Electrical Engineering, National Taiwan Normal University, Taipei 106, Taiwan.
  • Hao-Chieh Chang
    Graduate Institute of Clinical Dentistry, School of Dentistry, College of Medicine, National Taiwan University, Taipei, Taiwan.
  • Chin-Hao Chang
    Department of Medical Research, National Taiwan University Hospital, Taipei, Taiwan.
  • Po-Chun Chang
    Graduate Institute of Clinical Dentistry, School of Dentistry, College of Medicine, National Taiwan University, Taipei, Taiwan.

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