The psc-CVM assessment system: A three-stage type system for CVM assessment based on deep learning.

Journal: BMC oral health
PMID: 37573308

Abstract

BACKGROUND: Many scholars have proven cervical vertebral maturation (CVM) method can predict the growth and development and assist in choosing the best time for treatment. However, assessing CVM is a complex process. The experience and seniority of the clinicians have an enormous impact on judgment. This study aims to establish a fully automated, high-accuracy CVM assessment system called the psc-CVM assessment system, based on deep learning, to provide valuable reference information for the growth period determination.

Authors

  • Hairui Li
  • Haizhen Li
    Department of Orthodontics, Peking University School and Hospital of Stomatology, 22 Zhongguancun South Avenue, Haidian District, Beijing, P.R. China.
  • Lingjun Yuan
    Department of Orthodontics, Shanghai Ninth People's Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
  • Chao Liu
    Anti-Drug Technology Center of Guangdong Province, National Anti-Drug Laboratory Guangdong Regional Center, Guangzhou 510230, China.
  • Shengzhao Xiao
    Department of Orthodontics, Shanghai Ninth People's Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
  • Zhen Liu
    School of Pharmacy, Fudan University, PR China; Analytical Service Unit, WuXi AppTec (Shanghai) Co., Ltd, Shanghai, 200131, PR China.
  • Guoli Zhou
    Department of Orthodontics, Shanghai Ninth People's Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
  • Ting Dong
    Institute of Medical Imaging, University of Shanghai for Science and Technology, Shanghai 200093, P.R.China.
  • Ningjuan Ouyang
    Department of Orthodontics, Shanghai Ninth People's Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
  • Lu Liu
    College of Pharmacy, Harbin Medical University, Harbin, China.
  • Chenglong Ma
    Chohotech Inc, Hangzhou, China.
  • Yang Feng
    Computational Health Research Branch, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
  • Youyi Zheng
  • Lunguo Xia
    Department of Orthodontics, Shanghai Ninth People's Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China. xialunguo@hotmail.com.
  • Bing Fang
    Department of Orthodontics, Shanghai Ninth People's Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China. fangbing@sjtu.edu.cn.

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