Tooth model reconstruction based upon data fusion for orthodontic treatment simulation.

Area of Science:

• Biomedical Engineering
• Dental Technology
• Medical Imaging

Background:

• Traditional dental diagnostics rely on plaster models, which lack internal anatomical detail.
• Computed tomography (CT) offers comprehensive internal information crucial for advanced dental treatments.
• Existing methods for creating precise digital dental models are insufficient.

Purpose of the Study:

• To develop a high-quality, precise full tooth reconstruction method.
• To integrate 3D scanner data with CT image sets for comprehensive dental modeling.
• To enhance digital dental models for improved treatment planning.

Main Methods:

• Digitizing plaster models using a 3D scanner.
• Processing CT images for feature enhancement, noise reduction, and root slicing.
• Utilizing level set algorithm for root outline determination and ICP algorithm for data registration.
• Reconstructing complete digital dental models with the Delaunay-based region-growing (DBRG) algorithm.

Main Results:

• Successful integration of external scan data and CT images.
• Generation of detailed digital dental models including root information.
• Demonstration of a method for high-quality customized dental model reconstruction.

Conclusions:

• The proposed method enables the reconstruction of high-quality, customized digital dental models.
• This technique significantly aids in the planning of dental implant and orthodontic treatments.
• The data fusion approach provides a more complete representation of tooth anatomy compared to traditional methods.