基于三维人脸模板的颜面解剖标志点自动定点方法初探

Preliminary study on the method of automatically determining facial landmarks based on three-dimensional face template

目的探讨建立一种高效、自动确定三维数据颜面解剖标志点(简称标志点)的方法,并对该方法的定点效果进行初步评价。方法选取2021年6至8月于北京大学口腔医学院·口腔医院修复科就诊的牙体缺损或缺失男性患者(面部对称性良好)30例,年龄18~45岁;采集患者三维颜面数据,基于普氏分析算法进行尺寸归一化和重叠对齐。在Geomagic Studio 2013软件中构建三维人脸平均模型,并通过参数化处理构建三维人脸模板,使用MeshLab 2020软件在其上确定32个标志点序号(10个中线标志点和22个双侧标志点)。选取2021年6至8月于北京大学口腔医学院·口腔医院正畸科或口腔颌面外科就诊的下颌无偏斜和下颌轻度偏斜男性患者各5例,获取患者三维颜面数据作为测试数据,基于三维人脸模板及其标志点序号,借助MeshMonk非刚性配准算法程序自动确定测试数据32个标志点坐标,作为模板法定点数据。由同一名主治医师人工确定测试数据32个标志点位置,记录标志点坐标作为专家法定点数据。计算模板法与专家法标志点距离,作为定点误差,评价模板法的定点效果。结果对于5例下颌无偏斜患者,模板法所有标志点的定点误差为(1.65±1.19)mm,其中中线标志点的定点误差为(1.19±0.45)mm,双侧标志点的定点误差为(1.85±1.33)mm。对于5例下颌轻度偏斜患者,模板法所有标志点的定点误差为(2.55±2.22)mm,其中中线标志点的定点误差为(1.85±1.13)mm,双侧标志点的定点误差为(2.87±2.45)mm。结论本项研究提出的通过三维人脸模板自动确定标志点的方法具有一定的可行性,其对中线标志点的定点效果优于双侧标志点,对下颌无偏斜患者标志点的定点效果优于下颌轻度偏斜患者。

Objective To explore the establishment of an efficient and automatic method to determine anatomical landmarks in three-dimensional(3D)facial data,and to evaluate the effectiveness of this method in determining landmarks.Methods A total of 30 male patients with tooth defect or dentition defect(with good facial symmetry)who visited the Department of Prosthodontics,Peking University School and Hospital of Stomatology from June to August 2021 were selected,and these participants′age was between 18-45 years.3D facial data of patients was collected and the size normalization and overlap alignment were performed based on the Procrustes analysis algorithm.A 3D face average model was built in Geomagic Studio 2013 software,and a 3D face template was built through parametric processing.MeshLab 2020 software was used to determine the serial number information of 32 facial anatomical landmarks(10 midline landmarks and 22 bilateral landmarks).Five male patients with no mandibular deviation and 5 with mild mandibular deviation were selected from the Department of Orthodontics or Oral and Maxillofacial Surgery,Peking University School and Hospital of Stomatology from June to August 2021.3D facial data of patients was collected as test data.Based on the 3D face template and the serial number information of the facial anatomical landmarks,the coordinates of 32 facial anatomical landmarks on the test data were automatically determined with the help of the MeshMonk non-rigid registration algorithm program,as the data for the template method to determine the landmarks.The positions of 32 facial anatomical landmarks on the test data were manually determined by the same attending physician,and the coordinates of the landmarks were recorded as the data for determining landmarks by the expert method.Calculated the distance value of the coordinates of facial anatomical landmarks between the template method and the expert method,as the landmark localization error,and evaluated the effect of the template method in determining the landmarks.Results For 5 patients with no mandibular deviation,the landmark localization error of all facial anatomical landmarks by template method was(1.65±1.19)mm,the landmark localization error of the midline facial anatomical landmarks was(1.19±0.45)mm,the landmark localization error of bilateral facial anatomical landmarks was(1.85±1.33)mm.For 5 patients with mild mandibular deviation,the landmark localization error of all facial anatomical landmarks by template method was(2.55±2.22)mm,the landmark localization error of the midline facial anatomical landmarks was(1.85±1.13)mm,the landmark localization error of bilateral facial anatomical landmarks was(2.87±2.45)mm.Conclusions The automatic determination method of facial anatomical landmarks proposed in this study has certain feasibility,and the determination effect of midline facial anatomical landmarks is better than that of bilateral facial anatomical landmarks.The effect of determining facial anatomical landmarks in patients without mandibular deviation is better than that in patients with mild mandibular deviation.