Accuracy Evaluation of a Three-Dimensional Face Reconstruction Model Based on the Hifi3D Face Model and Clinical Two-Dimensional Images

Three-dimensional (3D) facial models have been increasingly applied in orthodontics, orthognathic surgery, and various medical fields. This study proposed an approach to reconstructing 3D facial models from standard orthodontic frontal and lateral images, providing an efficient way to expand 3D databases. A total of 23 participants (average age 20.70 ± 5.36 years) were enrolled. Based on the Hifi3D face model, 3D reconstructions were generated and compared with corresponding face scans to evaluate their accuracy. Root mean square error (RMSE) values were calculated for the entire face, nine specific facial regions, and eight anatomical landmarks. Clinical feasibility was further assessed by comparing six angular and thirteen linear measurements between the reconstructed and scanned models. The RMSE of the reconstruction model was 2.00 ± 0.38 mm (95% CI: 1.84-2.17 mm). High accuracy was achieved for the forehead, nose, upper lip, paranasal region, and right cheek (mean RMSE < 2 mm). The forehead area showed the smallest deviation, at 1.52 ± 0.88 mm (95% CI: 1.14-1.90 mm). In contrast, the lower lip, chin, and left cheek exhibited average RMSEs exceeding 2 mm. The mean deviation across landmarks was below 2 mm, with the Prn displaying the smallest error at 1.18 ± 1.10 mm (95% CI: 0.71-1.65 mm). The largest discrepancies were observed along the Z-axis (Z > Y > X). Significant differences (<i>p</i> < 0.05) emerged between groups in the nasolabial, nasal, and nasofrontal angles, while the other 13 linear and 3 angular measurements showed no statistical differences (<i>p</i> > 0.05). This study explored the feasibility of reconstructing accurate 3D models from 2D photos. Compared to facial scan models, the Hifi3D face model demonstrated a 2 mm deviation, with potential for enriching 3D databases for subjective evaluations, patient education, and communication. However, caution is advised when applying this model to clinical measurements, especially angle assessments.