系统仿真学报 ›› 2022, Vol. 34 ›› Issue (2): 376-384.doi: 10.16182/j.issn1004731x.joss.20-0758

• 国民经济仿真 • 上一篇    下一篇

基于目标区域约束的牙颌模型分割线探测方法

马天(), 李赟, 李娇娇, 李远成   

  1. 西安科技大学 计算机科学与技术学院,陕西 西安,710054
  • 收稿日期:2020-10-09 修回日期:2020-10-16 出版日期:2022-02-18 发布日期:2022-02-23
  • 作者简介:马天(1982-),男,博士,副教授,硕导,主要研究方向为图形图像处理、数据可视化。E-mail:matian@xust.edu.cn
  • 基金资助:
    国家自然科学基金(61834005);陕西省自然科学基础研究计划企业联合基金(2019JLM-11)

Segmentation Line Detection in Dental Model Based on Target Region Constraint

Tian Ma(), Yun Li, Jiaojiao Li, Yuancheng Li   

  1. College of Computer Science & Technology, Xi'an University of Science and Technology, Xi'an 710054, China
  • Received:2020-10-09 Revised:2020-10-16 Online:2022-02-18 Published:2022-02-23

摘要:

精确的将牙齿从牙颌模型中分割出来是虚拟牙齿矫正系统的一个重要的预处理问题。现有方法在进行牙颌模型分割时,多会对所有的面片直接进行计算处理。针对该问题,提出一种基于目标区域约束的分割线探测方法,可以将探测范围锁定在实际分割线的周围。该方法根据种子点的位置自动构建切割平面及切割线;通过寻找切割线上负曲率最大的位置来锁定探测范围;根据曲率及角度信息进行分割线的探测。实验结果表明,该方法对各类畸形牙模型的适应性更好,可在保证牙齿分割精度的同时,有效提高分割效率。

关键词: 虚拟牙齿矫正, 牙齿分割, 曲率特征, 分割线探测

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.

Key words: virtual orthodontics, teeth segmentation, curvature features, segmentation line detection

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