Author:
Mao Bochun,Li Jing,Tian Yajing,Zhou Yanheng
Abstract
Abstract
Background
This study aims to investigate the accuracy of a three-dimensional (3D) face reconstruction method based on conventional clinical two-dimensional (2D) photos.
Methods
Twenty-three patients were included, and Character Creator v3.2 software with the Headshot v1.0 plugin was used for 3D face model reconstruction. Various facial landmarks were finely adjusted manually to refine the models. After preprocessing and repositioning, 3D deviation analysis was performed. The accuracy of the landmarks in different dimensions was determined, and twelve facial soft tissue measurements were compared to validate the clinical potential of the method.
Result
The reconstructed 3D face models showed good facial morphology with fine texture. The average root mean square errors between face scan models and reconstructed models at perioral area (1.26 ± 0.24 mm, 95%CI: 1.15–1.37 mm) were significantly smaller than the entire facial area (1.77 ± 0.23 mm, 95%CI:1.67–1.88 mm), P < 0.01. The deviation of menton of soft tissue was significantly larger than pronasale (P < 0.01). The deviations of all landmarks in the Y-direction were significantly larger than those in the other 2 dimensions (Y > Z > X, P < 0.01). A significant difference (P < 0.05) of approximately 1.5 mm was found for facial height. Significant differences (P < 0.05) were also identified in the remaining 6 soft tissue measurements, with average deviations no greater than 0.5 mm (linear measurement) or 1.2° (angular measurements).
Conclusion
A 3D face modeling method based on 2D face photos was revealed and validated. The reconstruction accuracy of this method is clinically acceptable for orthodontic measurement purposes, but narrow clinical indications and labor-intensive operations remain problems.
Funder
National Natural Science Foundation of China
Research foundation of Peking University School and hospital of Stomatology
Publisher
Springer Science and Business Media LLC
Cited by
8 articles.
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