Objective: The aim of this study is to assess the accuracy of Procrustes analysis(PA)to compute a mid-sagittal
plane(MSP)of three-dimensional(3D) facial data.
Methods: Facial surface data from 30 subjects were acquired by a Face Scan optical 3D sensor. Using the data, 30
asymmetrical facial images with a true MSP for control purpose were constructed using the original facial image.
The MSPs of the 30 images are then computed using Procrustes analysis. The angle between the true-MSP and the
MSP obtained using the PA, and the asymmetry index serve as measures of assessing the accuracy of the
Procrustes analysis to compute the MSP of 3D facial data.
Results: The mean value and the standard deviation of the angle between the true-MSP and the PA-MSP are
0.62° and 0.49° respectively. The t-test for paired groups is used to assess the differences between the two MSPs in the
facial asymmetry index and P values of smaller than 0.05 are considered significant(t=0.783,p=0.440).
Conclusions: There are no significant differences between the PA-MSP and the true-MSP in terms of the
asymmetry index of the 30 subjects. Thus the Procrustes analysis can be used to compute the MSP of 3D facial
data with a significant degree of accuracy.
<strong>Objective</strong>: To evaluate the measurement accuracy of three-dimensional (3D) facial scanners for facial deformity patients from oral clinic. <strong>Methods</strong>: 10 patients in different types of facial deformity from oral clinical were included. Three 3D digital face models for each patient were obtained by three facial scanners separately (line laser scanner from Faro for reference, stereophotography scanner from 3dMD and structured light scanner from FaceScan for test). For each patient, registration based on Iterative Closest Point (ICP) algorithm was executed to align two test models (3dMD data & Facescan data) to the reference models (Faro data in high accuracy) respectively. The same boundaries on each pair models (one test and one reference models) were obtained by projection function in Geomagic Stuido 2012 software for trimming overlapping region, then 3D average measurement errors (3D errors) were calculated for each pair models also by the software. Paired t-test analysis was adopted to compare the 3D errors of two test facial scanners (10 data for each group). 3D profile measurement accuracy (3D accuracy) that is integrated embodied by average value and standard deviation of 10 patients’ 3D errors were obtained by surveying analysis for each test scanner finally. Results: 3D accuracies of 2 test facial scanners in this study for facial deformity were 0.44±0.08 mm and 0.43±0.05 mm. The result of structured light scanner was slightly better than stereophotography scanner. No statistical difference between them. <strong>Conclusions</strong>: Both test facial scanners could meet the accuracy requirement (0.5mm) of 3D facial data acquisition for oral clinic facial deformity patients in this study. Their practical measurement accuracies were all slightly lower than their nominal accuracies.