Orthodontic Collision Detection Using 3D Point Clouds

The patent segments the continuous 3D tooth movement trajectory into discrete time intervals or stages. At each stage, collision detection is performed independently using simplified 2D cross-sectional views rather than analyzing the entire 3D model continuously. This segmentation reduces computational complexity while maintaining collision detection accuracy.

The patent extracts critical geometric features from the full 3D digital model, such as tooth contours, contact points, and trajectory key positions. By working with these extracted features rather than the complete high-resolution 3D model, the system achieves accurate collision detection with reduced computational burden.

The patent employs dynamic adaptive mesh refinement where the 3D mesh resolution is adjusted based on the specific requirements of each tooth movement stage. In regions where collision risk is high or movement is complex, higher mesh density is used. In stable regions with simple movement, lower mesh density suffices. This dynamic adaptation maintains treatment planning precision while significantly reducing overall processing time.

The patent applies full-resolution 3D mesh modeling only where necessary for accurate collision detection, such as at potential contact zones between teeth. In other regions where collision risk is minimal, simplified geometric representations are used. This partial application of high-fidelity modeling maintains precision where needed while reducing processing time overall.