Zou Bei-ji, Liu Shi-jian, Liao Sheng-hui, Ding Xi, Liang Ye
School of Information Science and Engineering, Central South University, Changsha, PR China.
Department of Stomatology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, PR China.
Comput Biol Med. 2015 Jan;56:132-44. doi: 10.1016/j.compbiomed.2014.10.013. Epub 2014 Nov 13.
The accurate tooth partition of dental mesh is a crucial step in computer-aided orthodontics. However, tooth boundary identification is not a trivial task for tooth partition, since different shapes and their arrangements vary substantially among common clinical cases. Though curvature field is traditionally used for identifying boundaries, it is normally not reliable enough. Other methods may improve the accuracy, but require intensive user interaction. Motivated by state-of-the-art general interactive mesh segmentation methods, this paper proposes a novel tooth-target partition framework that employs harmonic fields to partition teeth accurately and effectively. In addition, a refining strategy is introduced to successfully segment teeth from the complicated dental model with indistinctive tooth boundaries on its lingual side surface, addressing an issue that had not been solved properly before. To utilise high-level information provided by the user, smart and intuitive user interfaces are also proposed with minimum interaction. In fact, most published interactive methods specifically designed for tooth partition are lacking efficient user interfaces. Extensive experiments and quantitative analyses show that our tooth partition method outperforms the state-of-the-art approaches in terms of accuracy, robustness and efficiency.
牙科网格的精确牙齿分割是计算机辅助正畸中的关键步骤。然而,牙齿边界识别对于牙齿分割而言并非易事,因为在常见临床病例中,不同牙齿的形状及其排列差异很大。尽管传统上使用曲率场来识别边界,但它通常不够可靠。其他方法可能会提高准确性,但需要大量用户交互。受最新的通用交互式网格分割方法的启发,本文提出了一种新颖的牙齿目标分割框架,该框架利用调和场准确有效地分割牙齿。此外,还引入了一种细化策略,以成功地从舌侧表面牙齿边界不清晰的复杂牙科模型中分割牙齿,解决了一个以前未得到妥善解决的问题。为了利用用户提供的高级信息,还提出了具有最少交互的智能直观用户界面。事实上,大多数专门为牙齿分割设计的已发表交互式方法都缺乏高效的用户界面。大量实验和定量分析表明,我们的牙齿分割方法在准确性、鲁棒性和效率方面优于现有方法。