Evolution of deep learning tooth segmentation from CT/CBCT images: a systematic review and meta-analysis.

Journal: BMC oral health
Published Date: May 26, 2025

Abstract

BACKGROUND: Deep learning has been utilized to segment teeth from computed tomography (CT) or cone-beam CT (CBCT). However, the performance of deep learning is unknown due to multiple models and diverse evaluation metrics. This systematic review and meta-analysis aims to evaluate the evolution and performance of deep learning in tooth segmentation.

Authors

  • Wai Ying Kot
    Faculty of Dentistry, The University of Hong Kong.
  • Sum Yin Au Yeung
    Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.
  • Yin Yan Leung
    Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.
  • Pui Hang Leung
    Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.
  • Wei-Fa Yang
    Division of Oral and Maxillofacial Surgery, Faculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region.

Keywords

External Resources

Popular Topics
Recent Journals