计算机应用 ›› 2017, Vol. 37 ›› Issue (3): 844-848.DOI: 10.11772/j.issn.1001-9081.2017.03.844

• 计算机视觉与虚拟现实 • 上一篇    下一篇

基于特征线分段技术的牙齿分割算法

肖兵, 魏昕, 胡伟, 夏鸿建   

  1. 广东工业大学 机电工程学院, 广州 510006
  • 收稿日期:2016-07-18 修回日期:2016-08-20 出版日期:2017-03-10 发布日期:2017-03-22
  • 通讯作者: 肖兵
  • 作者简介:肖兵(1991-),男,湖北十堰人,硕士研究生,主要研究方向:计算机图形学、计算机辅助生物医学工程;魏昕(1964-),女,江西南昌人,教授,博士,主要研究方向:精密与超精密加工、计算机辅助设计与制造;胡伟(1978-),男,湖北黄冈人,讲师,博士,主要研究方向:精密与超精密加工、计算机辅助设计与制造;夏鸿建(1978-),男,江西上饶人,讲师,博士,主要研究方向:参数化设计、智能计算机辅助设计。
  • 基金资助:
    国家自然科学基金资助项目(51175092);广东省自然科学基金资助项目(10151009001000036)。

Tooth segmentation algorithm based on segmentation of feature line

XIAO Bing, WEI Xin, HU Wei, XIA Hongjian   

  1. School of Electro-mechanical Engineering, Guangdong University of Technology, Guangzhou Guangdong 510006, China
  • Received:2016-07-18 Revised:2016-08-20 Online:2017-03-10 Published:2017-03-22
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (51175092), the Natural Science Foundation of Guangdong Province (10151009001000036).

摘要: 牙齿分割是计算机口腔正畸的重要技术,针对三维牙颌模型直接进行牙齿分割而不对齿间融合区域进行处理会存在精确度较差、缺失侧面形状的问题,以及现有牙齿形状建模方法交互多、效率低的问题,提出一种基于特征线分段技术的牙齿分割算法。根据曲率信息筛选特征区域并采用形态学算法提取牙列特征线;结合特征线分段和分支点匹配算法以及形态学膨胀操作实现齿间融合区域的自动识别;利用匹配的分支点对齿间孔洞搭桥修补,实现牙齿形状的自动恢复;提取齿间龈缘线,然后以所有龈缘线作为牙齿分割线分离出单颗牙齿。实验结果表明,该算法不仅能准确分离出具有侧面形状的单颗牙齿,而且避免了牙齿形状建模时的交互操作,而且与手动识别并删除齿间粘连区域、采用曲面能量约束方式重建齿间缺失曲面的方法相比,提高了牙齿分割效率60%~90%。

关键词: 三维牙颌模型, 牙齿分割, 牙齿形状建模, 形态学, 融合区域

Abstract: Tooth segmentation plays an important role in computer-aided orthodontics. However, many published approaches directly separate teeth from dental mesh without dealing with the region fusion, which leads to inaccurate results and incomplete segmented teeth with side shape lacked. Meanwhile, existing tooth shape modeling schemes are interaction-intensive and inefficient. To resolve this problem, a new tooth segmentation approach based on segmentation of feature line was proposed. Feature region was selected according to mean curvature, and morphologic algorithm was used to extract dentition line. The fusion region was automatically recognized by the feature line segmenting and branch points matching algorithm as well as morphologic dilation. The restoration result was automatically obtained by repairing holes with matched branch points. After the gingival margin lines between adjacent teeth were extracted, the teeth were segmented by all the gingival margin lines. Experimental results demonstrate that the poposed approach is accurate, the segmented teeth have complete side feature. In addition, the approach avoids user interactions in the stage of tooth shape modeling, thus improving the whole efficience by 60%-90% compared with the method which manually identifies and removes the interdental adhesion area and reconstructs the missing tooth surface by surface energy constraint.

Key words: three-dimensional dental model, tooth segmentation, tooth shape modeling, morphology, fusion area

中图分类号: