Computer-aided modelling of three-dimensional maxillofacial tissues through multi-modal imaging.

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Oral and Maxillofacial Surgery

Background:

• Digital imaging advancements enable 3D capture of anatomical tissues.
• Oral rehabilitation requires integrated data of soft facial tissue, facial skeleton, and dentition (maxillofacial triad).
• Current imaging techniques cannot capture the complete maxillofacial triad accurately.

Purpose of the Study:

• To present a multi-modal framework for creating an integrated 3D virtual maxillofacial model.
• To combine different digital imaging techniques for comprehensive anatomical data capture.
• To improve prediction of surgical and orthodontic outcomes in oral rehabilitation.

Main Methods:

• Developed a multi-modal framework for image fusion of digital techniques.
• Combined structured light surface scanning and cone-beam computed tomography data.
• Aligned different tissue data based on common anatomical constraints to create a fused 3D model.

Main Results:

• Successfully created a 3D virtual maxillofacial model integrating photorealistic face, facial skeleton, and dentition.
• The fusion procedure enabled multi-modal representations of the maxillofacial triad.
• The framework allows for accurate alignment of diverse anatomical data.

Conclusions:

• The presented multi-modal framework successfully integrates various digital imaging techniques.
• This approach creates a comprehensive 3D virtual model of the maxillofacial triad.
• The integrated model holds significant potential for enhancing oral rehabilitation planning and outcome prediction.