Morphology and mechanical performance of dental crown designed by 3D-DCGAN.

Journal: Dental materials : official publication of the Academy of Dental Materials
PMID: 36822895

Abstract

OBJECTIVES: This study utilised an Artificial Intelligence (AI) method, namely 3D-Deep Convolutional Generative Adversarial Network (3D-DCGAN), which is one of the true 3D machine learning methods, as an automatic algorithm to design a dental crown.

Authors

  • Hao Ding
  • Zhiming Cui
    The Institute of Information Processing and Application, Soochow University, Suzhou 215006, China.
  • Ebrahim Maghami
    Department of Mechanical Engineering and Mechanics, College of Engineering, Drexel University, Philadelphia, USA.
  • Yanning Chen
    School of International Studies, Hunan Institute of Technology, Hengyang 421002, China.
  • Jukka Pekka Matinlinna
    Dental Materials Science, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong; Division of Dentistry, School of Medical Sciences, The University of Manchester, Manchester, UK.
  • Edmond Ho Nang Pow
    Clinical Associate Professor in Prosthodontics, Restorative Dental Sciences, Faculty of Dentistry, the University of Hong Kong, Hong Kong Special Administrative Region, PR China.
  • Alex Siu Lun Fok
    Minnesota Dental Research Center for Biomaterials and Biomechanics, School of Dentistry, University of Minnesota, USA.
  • Michael Francis Burrow
    Restorative Dental Sciences, Faculty of Dentistry, The University of Hong Kong, Hong Kong.
  • Wenping Wang
    School of Management Science and Engineering, Shandong Normal University, Jinan, China.
  • James Kit Hon Tsoi
    Dental Materials Science, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong. Electronic address: jkhtsoi@hku.hk.

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