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

Yujia Zhu; Lingxiao Zhang; Shuzhi Liu; Aonan Wen; Zixiang Gao; Qingzhao Qin; Lin Gao; Yijiao Zhao; Yong Wang

doi:10.1016/j.jdent.2024.105043

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

J Dent. 2024 May 10:105043. doi: 10.1016/j.jdent.2024.105043. Online ahead of print.

Authors

Yujia Zhu¹, Lingxiao Zhang², Shuzhi Liu², Aonan Wen¹, Zixiang Gao¹, Qingzhao Qin¹, Lin Gao³, Yijiao Zhao⁴, Yong Wang⁵

Affiliations

¹ Center of Digital Dentistry, Peking University School and Hospital of Stomatology; National Engineering Laboratory for Digital and material technology of stomatology; NHC Key Laboratory of Digital technology of stomatology; Beijing Key Laboratory of Digital Stomatology; National Clinical Research Center for Oral Diseases.
² Institute of Computing Technology, Chinese Academy of Sciences.
³ Institute of Computing Technology, Chinese Academy of Sciences. Electronic address: gaolin@ict.ac.cn.
⁴ Center of Digital Dentistry, Peking University School and Hospital of Stomatology; National Engineering Laboratory for Digital and material technology of stomatology; NHC Key Laboratory of Digital technology of stomatology; Beijing Key Laboratory of Digital Stomatology; National Clinical Research Center for Oral Diseases. Electronic address: kqcadcs@bjmu.edu.cn.
⁵ Center of Digital Dentistry, Peking University School and Hospital of Stomatology; National Engineering Laboratory for Digital and material technology of stomatology; NHC Key Laboratory of Digital technology of stomatology; Beijing Key Laboratory of Digital Stomatology; National Clinical Research Center for Oral Diseases. Electronic address: kqcadc@bjmu.edu.cn.

PMID: 38735469
DOI: 10.1016/j.jdent.2024.105043

Abstract

Objectives: Three-dimensional (3D) facial symmetry analysis is based on the 3D symmetry reference plane (SRP). Artificial intelligence 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 enrolled. 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° and 0.99° 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 an innovative 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.

Keywords: Artificial Intelligence (AI) ;deep learning; FaceSCAN; Three-dimensional facial data; facial planar reflective symmetry net; symmetry reference plan.