Segmentation Line Detection in Dental Model Based on Target Region Constraint

doi:10.16182/j.issn1004731x.joss.20-0758

Abstract

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

CLC Number:

TP391.9

Tian Ma, Yun Li, Jiaojiao Li, Yuancheng Li. Segmentation Line Detection in Dental Model Based on Target Region Constraint[J]. Journal of System Simulation, 2022, 34(2): 376-384.

Figures/Tables 15

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Fig. 10

Table 1

Fig. 11

Fig. 12

Table 2

Table 3

References 16

1	常同辉. 基于机器学习的复杂曲面特征提取与分割方法及其应用研究[D]. 杭州: 浙江大学, 2017.
	Chang Tonghui. Machine Learning Based Complex Surface Feature Extraction and Segmentation Method and Its Applications[D]. Hangzhou: ZhejiangUniversity, 2017.
2	Kondo T, Ong S H, Foong K W C. Tooth Segmentation of Dental Study Models using Range Images[J]. IEEE Transactions on Medical Imaging(S2168-3085), 2004, 23(3): 350362.
3	Grzegorzek M, Trierscheid M, Papoutsis D, et al. A Multi-stage Approach for 3D Teeth Segmentation from Dentition Surfaces[C]// Image and Signal Processing, 4th International Conference, ICISP2010, Trois-Rivières, QC, Canada, June 30-July 2, 2010. Proceedings. Springer-Verlag, 2010.
4	马勇, 柯永振, 杨帅. 基于网格抽取的牙齿模型快速分割算法[J].计算机应用与软件, 2018, 35(5): 247-252.
	Ma Yong, Ke Yongzhen, Yang Shuai. A Tooth Model Fast Segmentation Algorithm based on Mesh Extraction[J]. Computer Applications and Software, 2018, 35(5): 247-252.
5	赵夫群, 周明全. 一种有效的兵马俑碎块断裂面分割方法[J]. 图学学报, 2017, 38(4): 504-508.
	Zhao Fuquan, Zhou Mingquan. An Effective Fracture Surface Segmentation Method of the Terracotta Warrior Block[J]. Journal of Graphics, 2017, 38(4): 504-508.
6	高天一, 韩慧妍, 韩燮. 基于骨架的三维点云模型分割[J]. 计算机工程与设计, 2019, 40(5): 1418-1423.
	Gao Tianyi, Han Huiyan, Han Xian. Skeleton-based Three-dimensional Point Cloud Model Segmentation[J]. Computer Engineering and Design, 2019, 40(5): 1418-1423.
7	Wang H, Li Z. Interactive Tooth Separation from Dental Model Using Segmentation Field[C]// Engineering in Medicine & Biology Society, IEEE, 2016: 5616-5619.
8	Zou B J, Liu S J, Liao S H, et al. Interactive Tooth Partition of Dental Mesh base on Tooth-target Harmonic Field[J]. Computers in Biology & Medicine(S0010-4825), 2015, 56:132-144.
9	Sheng-Hui L, Shi-Jian L, Bei-Ji Z, et al. Automatic Tooth Segmentation of Dental Mesh Based on Harmonic Fields[J]. Biomed Research International(S2314-6133), 2015: 187173.
10	张耀楠, 周升, 牛乐川, 等. 一种基于蚁群优化的网格分割方法[J]. 计算机工程, 2018, 44(2): 277-281.
	Zhang Yaonan, Zhou Sheng, Niu Lechuan. A Mesh Segmentation Method Based on Ant Colony Optimization[J]. Computer Engineering, 2018, 44(2): 277-281.
11	肖兵, 魏昕, 胡伟, 等. 基于特征线分段技术的牙齿分割算法[J]. 计算机应用, 2017, 37(3): 844-848.
	Xiao Bing, Wei Xin, Hu Wei, et al. Tooth Segmentation algorithm based on Segmentation of Feature Line[J]. Journal of Computer Applications, 2017, 37(3): 844-848.
12	吴婷, 张礼兵. 3维牙颌模型牙齿分割的路径规划方法[J]. 中国图象图形学报, 2018, 23(1): 84-94.
	Wu Ting, Zhang Libing.Tooth Segmentation on 3D Dental Meshes Based on Path Planning[J].Journal of Image and Graphics, 2018, 23(1): 84-94.
13	Zhang Jianda, Li Chunpeng, Song Qiang, et al. Automatic 3D Tooth Segmentation using Convolutional Neural Networks in Harmonic Parameter Space[J]. Graphical Models(S1524-0703), 2020, 109: 101071.
14	褚玉伟, 罗晓博, 屈珂, 等. DBSCAN和K-Means混合聚类的牙齿特征自动识别[J]. 计算机辅助设计与图形学学报, 2018, 30(7): 1276-1283.
	Zhu Yuwei, Luo Xiaobo, Qu Ke, et al. DBSCAN and K-Means Hybrid Clustering Based Automatic Dental Feature Detection[J]. Journal of Computer-Aided Design & Computer Graphics, 2018, 30(7): 1276-1283.
15	李成军, 张弛, 汪国平. 交互标记控制的快速网格分割[J]. 北京大学学报(自然科学版), 2006(5): 662-667.
	Li Chengjun, Zhang Chi, Wang Guoping. Fast Marker-Controlled Interactive Mesh Segmentation[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2006(5): 662-667.
16	姜晓通, 戴宁, 张长东, 等. 牙齿半自动精确分割算法[J]. 计算机辅助设计与图形学学报, 2020, 32(5): 820-829.
	Jiang Xiaotong, Dai Ning, Zhang Changdong, et al. A Semi-Automatic Precise Tooth Segmentation Algorithm of Dental Model[J]. Journal of Computer-Aided Design & Computer Graphics, 2020, 32(5): 820-829.

网格模型（顶点数）	切割面	切割线	分割线初始点	分割线探测	总计
1（15~20万）	3.062	0.155	5.262	2.976	12.455
2（10~15万）	2.206	0.083	4.370	2.354	9.013
2（5~10万）	1.328	0.031	3.985	1.831	7.175
3（3~5万）	0.875	0.047	2.609	1.808	5.339

算法	一阶邻域	二阶邻域	三阶邻域
本文算法	75	86	91
文献[1]算法	80	87	93

网格模型(顶点数)	耗时/s		提升率/%
网格模型(顶点数)	本文算法	文献[1]	提升率/%
1(3~5万)	7.17	12.84	44
2(5~10万)	9.21	20.35	54
3(10~15万)	10.37	26.74	61
4(15~20万)	16.69	45.20	63

[1]	Huang Tao, Zhang Zhi, Ding Yujie, Chen Yanbo, Wang Jing, Zhang Wenqian. Robust Emergency Dispatch Method Considering Dynamic Frequency Security and N-k Contingency [J]. Journal of System Simulation, 2025, 37(12): 2981-2993.
[2]	Zhang Runzhao, Chen Yanbo, Huang Tao, Tian Haoxin, Qiang Tuben, Zhang Zhi. Scheduling Method for Virtual Power Plants Based on Analysis and Forecasting of Heterogeneous Load Characteristics [J]. Journal of System Simulation, 2025, 37(12): 2994-3006.
[3]	Yu Xiangxing, Zhao Yandong, Zhang Baolin. Vibration Control of Offshore Wind Turbine Towers Based on Eddy Current Nonlinear Energy Sink [J]. Journal of System Simulation, 2025, 37(12): 3007-3017.
[4]	Li Bin, Wang Yuchuo. Fault Diagnosis Method for Photovoltaic Systems Based on Multi-strategy Fusion [J]. Journal of System Simulation, 2025, 37(12): 3018-3032.
[5]	Li Xiaobin, Hu Bing, Yin Chao, Li Bo, Ma Jun. Spatiotemporal Graph Convolution-based Demand Forecasting and Simulation Analysis for Automotive Parts Supply Chain [J]. Journal of System Simulation, 2025, 37(12): 3060-3074.
[6]	Peng Yi, Lei Yunkui, Yang Qingqing, Li Hui, Wang Jianming. Improved PID Search Algorithm for UAV Path Planning in Mountainous Environments [J]. Journal of System Simulation, 2025, 37(12): 3075-3086.
[7]	Chen Yi, Qiu Sihang, Zhu Zhengqiu, Ji Yatai, Zhao Yong, Ju Rusheng. A Method of Heuristic Human-LLM Collaborative Source Search [J]. Journal of System Simulation, 2025, 37(12): 3112-3127.
[8]	Suo Jingyi, Lu Baihong, Qu Che. Measurement of Luminous Intensity Distribution for Film and Television LED Light Sources and Its Simulation Research in Game Engines [J]. Journal of System Simulation, 2025, 37(12): 3140-3151.
[9]	Gong Jianxing, Hu Hai, Ren Haihui, Wu Ruixiang. Interoperability Model and Application of Military Training System for Combination of Virtuality and Reality [J]. Journal of System Simulation, 2025, 37(12): 3161-3175.
[10]	Xu Zhixia, Wang Rui, Sun Nan, He Bing, Shen Xiaowei, Zhu Xiaofei. Research on Cooperative Interference Allocation of Jamming Resources Based on Improved Genetic Algorithm [J]. Journal of System Simulation, 2025, 37(12): 3176-3189.
[11]	Liu Xiang, Jin Qiankun. Research on PAC-Bayes-Based A2C Algorithm for Multi-objective Reinforcement Learning [J]. Journal of System Simulation, 2025, 37(12): 3212-3223.
[12]	Yang Lanying, Li Chao, Zou Haifeng, Wan Jiangtao, Zhang Renqiang, Liu Hui, Lu Hong. Robot Path Planning Optimization Based on Fusion of Improved Ant Colony Algorithm and A* Algorithm [J]. Journal of System Simulation, 2025, 37(11): 2956-2965.
[13]	Su Xiaoting, Zhang Xiaowei, Tian Yi, Li Qi, Wang Shuaihao. Research on Time Sequence Design Method of Dynamic Simulation Scene for Starlight Navigation [J]. Journal of System Simulation, 2025, 37(11): 2946-2955.
[14]	Zhang Zhili, Liu Jin, Zhou Zhaofa, Liang Zhe, Zhang Yunhao. Research on Temperature Compensation Technology of Fiber Optic Gyroscope based on ISCSO-BP Neural Network Model [J]. Journal of System Simulation, 2025, 37(11): 2904-2917.
[15]	Chen Jitong, Zhou Jiajia, Wu Di, Jiang Hailong. A USV Path Planning Algorithm under Special Environment Based on TD3-RRT [J]. Journal of System Simulation, 2025, 37(11): 2888-2903.