Automatic restoration and reconstruction of defective tooth based on deep learning technology.

Journal: BMC oral health
Published Date: Aug 2, 2025

Abstract

BACKGROUND: Accurate restoration and reconstruction of tooth morphology are crucial in restorative dentistry, implantology, and forensic odontology. Traditional methods, like manual wax modeling and template-based computer-aided design (CAD), struggle with accuracy, personalization, and efficiency. To address the challenge, we propose an innovative and efficient deep learning-based framework designed for the automatic restoration and reconstruction of tooth morphology.

Authors

  • Juhao Wu
    School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, 510006, China.
  • Yuanchang Huang
    School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, 510006, China.
  • Jiayan He
    School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, 510006, China.
  • Kunjing Chen
    School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, 510006, China.
  • Wenlong Wang
    The School of Electrical Engineering, Shanghai Dianji University, Shanghai 201306, China; Intelligent Decision and Control Technology Institute, Shanghai Dianji University, Shanghai 201306, China.
  • Xiao Li
    Department of Inner Mongolia Clinical Medicine College, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.

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