Segmentation Line Detection in Dental Model Based on Target Region Constraint

Abstract

It is an important pretreatment of a virtual orthodontic system to accurately segment teeth from a dental model. In the present methods, all patches are computed directly. To solve this problem, this paper proposes a segmentation line detection method based on target region constraint, which narrows down the detection range to the area around the actual segmentation line. In this method, the cutting plane and the cutting line are automatically formed according to the positions of seed points. The detection range is determined by the search for the position with the greatest negative curvature on the cutting line. The segmentation line is detected depending on curvature and angle information. The experimental results show that this method has strong adaptability to various malformed tooth models and can greatly improve the segmentation efficiency while ensuring the accuracy of teeth segmentation.