journal article·2025-01-24Open access

Reproducibility and Accuracy of Two Facial Scanners: A 3D In Vivo Study

Federica Pellitteri, Marta Calza, Giacomo Baldi, Matteo De Maio, Luca Lombardo

Applied Sciences· Volume 15· Issue 3

Abstract

Aim: This study aimed to compare the accuracy and reproducibility of the EinScan H2 (SHINING 3D, Hangzhou, China) with the Vectra M3 3D Imaging System (Canfield Scientific, Parsippany, NJ, USA) and with direct anthropometric measurements. Methods: Twenty subjects were scanned with two different facial scanning systems. Linear measurements were compared with direct anthropometric measurements taken on the patient’s face, while area analysis (forehead, tip of the nose, chin, right and left cheek) was performed by overlaying scans after best-fit alignment using the Geomagic Control X v2020.1.1 program. Statistical analysis was conducted using IBM SPSS v28 software, except for the power analysis, which was conducted using R v4.2.1. Results: The intraclass correlation coefficient (ICC) showed high repeatability for both the linear and point measurements, with all values exceeding 0.90. The paired-sample Wilcoxon test revealed no significant differences (p > 0.05) between the linear measurements, indicating consistency across the three measurement methods. Point analysis using the single-sample Wilcoxon test also showed no significant differences (p > 0.05) in the median values. The differences between the two scanning instruments for cephalometric points ranged from 0.5 mm to −0.5 mm, except for the subnasal point (0.73 mm). Over 70% of the surface areas analyzed showed overlapping within the highly reproducible range (0.5 mm to −0.5 mm). Conclusion: Both scanning systems investigated in this study proved to be accurate and reliable for capturing 3D images of the patient’s face.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Orthodontics and Dentofacial Orthopedics · Face recognition and analysis · 3D Shape Modeling and Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Orthodontics, University of Ferrara, 44121 Ferrara, Italy

School of Dentistry, University of Ferrara, 44121 Ferrara, Italy

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