Automatic Real-Time Space Registration Application for Simulating Dental and Maxillofacial Surgery.

Area of Science:

• Medical Imaging
• Computer-Aided Surgery
• Biomedical Engineering

Background:

• Real-time surgical navigation systems rely on accurate preoperative planning and intraoperative guidance.
• Existing automatic multimodal data registration methods lack accuracy, speed, and clinical applicability.
• Challenges include limited scope and practical limitations of current registration techniques.

Purpose of the Study:

• To develop a novel, accurate, and fast real-time teeth registration algorithm.
• To improve multimodal data registration for surgical navigation systems.
• To address limitations of existing methods in accuracy and clinical application.

Main Methods:

• Proposed a weighted iterative closest point (ICP) algorithm with three key improvements.
• Generated multilayer spherical point sets within laser scanning marker spheres.
• Integrated voxel center point set weights with computed tomography (CT) data for enhanced registration.
• Utilized real-time optical tracking for spatial registration and simulated surgical instrument navigation.

Main Results:

• The proposed ICP registration method significantly overcomes surface point set limitations and high surface deformity issues.
• Achieved a mean square error reduction of one order of magnitude compared to existing methods.
• Demonstrated strong practical value in multimodal fusion image-guided navigation.

Conclusions:

• The novel ICP algorithm offers superior accuracy and speed for real-time teeth registration.
• This method enhances the reliability and clinical applicability of surgical navigation systems.
• The approach holds significant potential for improving preoperative planning and intraoperative guidance in dental and maxillofacial surgeries.