Machine learning in dental, oral and craniofacial imaging: a review of recent progress

Ruiyang Ren; Haozhe Luo; Chongying Su; Yang Yao; Wen Liao

doi:10.7717/peerj.11451

Machine learning in dental, oral and craniofacial imaging: a review of recent progress

PeerJ. 2021 May 17:9:e11451. doi: 10.7717/peerj.11451. eCollection 2021.

Authors

Ruiyang Ren¹, Haozhe Luo², Chongying Su¹, Yang Yao³, Wen Liao^{4

5}

Affiliations

¹ State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China School of Stomatology, Sichuan University, Chengdu, Sichuan, China.
² School of Computer Science, Sichuan University, Chengdu, Sichuan, China.
³ State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, Department of Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China.
⁴ State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, Department of Orthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China.
⁵ Department of Orthodontics, Osaka Dental University, Hirakata, Osaka, Japan.

Abstract

Artificial intelligence has been emerging as an increasingly important aspect of our daily lives and is widely applied in medical science. One major application of artificial intelligence in medical science is medical imaging. As a major component of artificial intelligence, many machine learning models are applied in medical diagnosis and treatment with the advancement of technology and medical imaging facilities. The popularity of convolutional neural network in dental, oral and craniofacial imaging is heightening, as it has been continually applied to a broader spectrum of scientific studies. Our manuscript reviews the fundamental principles and rationales behind machine learning, and summarizes its research progress and its recent applications specifically in dental, oral and craniofacial imaging. It also reviews the problems that remain to be resolved and evaluates the prospect of the future development of this field of scientific study.

Keywords: Dental, oral and craniofacial imaging; Machine learning; Oral cancer; Orthodontics.

Grants and funding

This study was supported by the Science and Technology Department of Sichuan Province (20ZDYF2839) and 2018 Sichuan University-Luzhou City Co-operaton Program (CDLZ2018-14). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.