Development of three-dimensional facial expression models using morphing methods for fabricating facial prostheses.

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Prosthodontics

Background:

• Fabricating custom facial prostheses requires precise 3D models that accurately capture facial anatomy and expressions.
• Maintaining prosthesis fit, especially in mobile facial areas, is challenging with traditional modeling techniques.

Purpose of the Study:

• To develop a novel method for creating best-fit three-dimensional (3D) facial prosthesis models that incorporate dynamic facial expressions.
• To utilize time-series data and morphing techniques for generating accurate 3D facial expression models.

Main Methods:

• Digital acquisition of three distinct facial expressions (neutral, smile, open mouth) from seven normal subjects and seven patients with nasal defects using a facial scanner.
• Transformation of scanned data into homologous models with consistent topology and point cloud data.
• Generation of 3D facial expression models through morphing between homologous models and subsequent accuracy evaluation.

Main Results:

• Successful generation of 3D facial expression models for both normal subjects and patients with nasal defects.
• Demonstrated high accuracy, with no significant shape differences observed between scanned and homologous models.

Conclusions:

• The developed 3D facial expression modeling method exhibits high accuracy in both healthy individuals and patients.
• This technique shows significant potential for improving the fabrication of custom-fit facial prostheses, enhancing patient outcomes.