Automatic three-dimensional facial symmetry reference plane construction based on facial planar reflective symmetry net

doi:10.1016/j.jdent.2024.105043

	Automatic three-dimensional facial symmetry reference plane construction based on facial planar reflective symmetry net
	Zhu, Yujia 1,2,3,4,5; Zhang, Lingxiao 6; Liu, Shuzhi 6; Wen, Aonan 1,2,3,4,5; Gao, Zixiang 1,2,3,4,5; Qin, Qingzhao 1,2,3,4,5; Gao, Lin 6; Zhao, Yijiao 1,2,3,4,5; Wang, Yong 1,2,3,4,5
	2024-08-01
发表期刊	JOURNAL OF DENTISTRY
ISSN	0300-5712
卷号	147 页码:7
摘要	Objectives: Three-dimensional (3D) facial symmetry analysis is based on the 3D symmetry reference plane (SRP). Artificial intelligence (AI) is widely used in the dental and oral sciences. This study developed a novel deep learning model called the facial planar reflective symmetry net (FPRS-Net) to automatically construct an SRP and established a method for defining a 3D point-cloud region of interest (ROI) and high-dimensional feature computations suitable for this network model. Methods: Overall, 240 patients were enroled. The deep learning model was trained and predicted using 200 samples, and its clinical suitability was evaluated with 40 samples. Four FPRS-Net models were prepared, each using supervised and unsupervised learning approaches based on full facial and ROI data (FPRS-Net(S), FPRS-Net(SR), FPRS-Net(U), and FPRS-Net(UR)). These models were trained on 160 3D facial datasets, validated on 20 cases, and tested on another 20 cases. The model predictions were evaluated using an additional 40 clinical 3D facial datasets by comparing the mean square error of the SRP between the parameters predicted by the four FPRS-Net models and the truth plane. The clinical suitability of FPRS-Net models was evaluated by measuring the angle error between the predicted and ground-truth planes; experts evaluated the predicted SRP of the four FPRS-Net models using the visual analogue scales (VAS) method. Results: The FPRS-Net(SR) and FPRS-Net(U) models achieved an average angle error of 0.84 degrees and 0.99 degrees in predicting 3D facial SRP, respectively, with a VAS value of >8. Using the four FPRS-Net models to create an SRP in 40 cases of 3D facial data required <4 s. Conclusions: Our study demonstrated a new solution for automatically constructing oral clinical 3D facial SRPs. Clinical significance: This study proposes a novel deep learning algorithm (FPRS-Net) to construct a symmetry reference plane that can reduce workload, shorten the time required for digital design, reduce dependence on expert experience, and improve therapeutic efficiency and effectiveness in dental clinics.
关键词	Three-dimensional facial data FaceSCAN Artificial Intelligence (AI) Deep learning Symmetry reference plan Facial planar reflective symmetry net
DOI	10.1016/j.jdent.2024.105043
收录类别	SCI
语种	英语
资助项目	National Natural Science Founda- tion of China[82071171] ; National Natural Science Founda- tion of China[82271039] ; National Key R & D Program of China[2022YFC2405401] ; Natural Sci- ence Foundation of Beijing[L232100] ; Open Subject Foundation of Peking University Hospital of Stomatology[PKUSS20220301]
WOS研究方向	Dentistry, Oral Surgery & Medicine
WOS类目	Dentistry, Oral Surgery & Medicine
WOS记录号	WOS:001256155300001
出版者	ELSEVIER SCI LTD
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/39881
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Gao, Lin; Zhao, Yijiao; Wang, Yong
作者单位	1.Peking Univ, Ctr Digital Dent, Dept Prosthodont, Sch & Hosp Stomatol, Beijing, Peoples R China 2.Natl Ctr Stomatol, Beijing, Peoples R China 3.Natl Engn Res Ctr Oral Biomat & Digital Med Device, Beijing, Peoples R China 4.Beijing Key Lab Digital Stomatol, Beijing, Peoples R China 5.NHC Key Lab Digital Stomatol, Beijing, Peoples R China 6.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Zhu, Yujia,Zhang, Lingxiao,Liu, Shuzhi,et al. Automatic three-dimensional facial symmetry reference plane construction based on facial planar reflective symmetry net[J]. JOURNAL OF DENTISTRY,2024,147:7.
APA	Zhu, Yujia.,Zhang, Lingxiao.,Liu, Shuzhi.,Wen, Aonan.,Gao, Zixiang.,...&Wang, Yong.(2024).Automatic three-dimensional facial symmetry reference plane construction based on facial planar reflective symmetry net.JOURNAL OF DENTISTRY,147,7.
MLA	Zhu, Yujia,et al."Automatic three-dimensional facial symmetry reference plane construction based on facial planar reflective symmetry net".JOURNAL OF DENTISTRY 147(2024):7.