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Evaluation of Trueness and Precision in Extraoral 3D Facial Scanning Systems Using a 3D-Printed Head Model: An In
Viet Hoang1, Tue Huu Nguyen2, Trang Nhat Uyen Doan2
1Department of Orthodontics and Pedodontics, Faculty of Dentistry, Van Lang University, Ho Chi Minh City 70000, Vietnam.
Journal of Clinical Medicine
|December 11, 2025
Summary
This study compared four 3D facial scanning systems. The Polycam app offered the highest trueness, while the MetiSmile scanner provided the best precision for facial scanning.
Area of Science:
- Biomedical Engineering
- Dental Technology
- 3D Imaging
Background:
- Extraoral 3D facial scanning systems are increasingly used in dentistry and digital workflows.
- Evaluating the accuracy (trueness) and repeatability (precision) of these systems is crucial for clinical application.
- Standardized laboratory assessments are needed to compare different scanning technologies.
Purpose of the Study:
- To evaluate and compare the trueness and precision of four extraoral 3D facial scanning systems.
- To assess the suitability of handheld, desktop, and mobile-based scanners for clinical use.
- To provide quantitative data on the accuracy of commonly available facial scanning technologies.
Main Methods:
- A 3D-printed human head model with defined landmarks and distances was used as a reference.
- Four systems (MetiSmile handheld scanner, RAYFace desktop scanner, Heges mobile app, Polycam mobile app) were used to scan the model 15 times each.
- Caliper measurements served as the ground truth; digital measurements were analyzed for trueness and precision using statistical tests.
Main Results:
- Polycam achieved the highest trueness (0.49 ± 0.32 mm), followed by MetiSmile (0.51 ± 0.36 mm).
- MetiSmile demonstrated the highest precision (0.12 ± 0.07 mm), with Polycam also showing good precision (0.15 ± 0.06 mm).
- All systems showed mean deviations under 1 mm, with three systems achieving less than 0.6 mm accuracy.
Conclusions:
- Polycam and MetiSmile offer high trueness and precision, respectively, indicating clinical acceptability for educational and preliminary digital workflows.
- Both professional and mobile-based scanners can capture facial morphology with clinically acceptable deviations.
- Further validation in real clinical settings is recommended due to potential variations in motion, lighting, and soft tissues.

