国际口腔医学杂志

国际口腔医学杂志 ›› 2023, Vol. 50 ›› Issue (2): 146-151.doi: 10.7518/gjkq.2023033

• 人工智能专栏 • 上一篇    下一篇

基于机器学习的牙龄评测研究进展

唐粤亭1(),代佳琪2,董雯萱3,王虎1,郭际香3,游梦1()   

  1. 1.口腔疾病研究国家重点实验室;国家口腔疾病临床医学研究中心;四川大学华西口腔医院医学影像科 成都 610041
    2.四川口腔医院放射科 成都 610015
    3.四川大学计算机学院 成都 610065
  • 收稿日期:2022-07-29 修回日期:2022-11-10 出版日期:2023-03-01 发布日期:2023-03-14
  • 通讯作者: 游梦
  • 作者简介:唐粤亭，医师，硕士，Email：497315852@qq.com
  • 基金资助:
    四川大学华西口腔医院探索与研发项目(LCYJ2019-9)

Research progress of dental age evaluation based on machine learning methods

Tang Yueting1(),Dai Jiaqi2,Dong Wenxuan3,Wang Hu1,Guo Jixiang3,You Meng1()   

  1. 1.State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases & Dept. of Oral Medical Imaging, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
    2.Dept. of Oral Radiology, Sichuan Hospital of Stomatology, Chengdu 610015, China
    3.College of Computer Science, Sichuan University, Chengdu 610065, China
  • Received:2022-07-29 Revised:2022-11-10 Online:2023-03-01 Published:2023-03-14
  • Contact: Meng You
  • Supported by:
    Exploration and Research and Development Project of West China Hospital of Stomatology, Sichuan University(LCYJ2019-9)

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摘要：

牙龄是生物学年龄的一项重要指标，在口腔正畸学、牙科法医学、刑侦学等方面有重要的应用价值。牙龄评测的传统方法包括图谱法、计分法、牙髓腔增龄性评测法等，这些人工评测方法较为烦琐而影响其推广应用。随着人工智能和机器学习相关技术的发展，近年来出现了牙龄的智能评测相关研究，并在算法准确性等方面取得了一定的进展。本文对牙龄评测的传统方法和机器学习方法进行总结，归纳了在探索及实践过程中传统方法与现代方法的优势和不足， 旨在为牙龄评测的后续研究和应用提供参考。

关键词: 牙龄, 牙龄评测, 机器学习, 人工智能

Abstract:

Dental age is an important indicator of biological age and has essential application value in orthodontics, forensic dentistry, and criminal investigation. Traditional methods of dental age evaluation include atlas, scoring, and pulp cavity evaluation. These manual evaluation methods are relative cumbersome that their applications have been hampered. With the development of artificial intelligence technology and machine learning algorithms, intelligent evaluation of dental age have been gained more attention in recent years. This paper aims to provide a reference for the future research and application of dental age evaluation, summarize traditional and machine learning methods, and demonstrate the benefits and limitations of the existing approaches that are used in this topic.

Key words: dental age, dental age assessment, machine learning, artificial intelligence

中图分类号: 

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