Journal of System Simulation
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.
Recommended Citation
Ma, Tian; Li, Yun; Li, Jiaojiao; and Li, Yuancheng
(2022)
"Segmentation Line Detection in Dental Model Based on Target Region Constraint,"
Journal of System Simulation: Vol. 34:
Iss.
2, Article 20.
DOI: 10.16182/j.issn1004731x.joss.20-0758
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol34/iss2/20
First Page
376
Revised Date
2020-10-16
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.20-0758
Last Page
384
CLC
TP391.9
Recommended Citation
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.
DOI
10.16182/j.issn1004731x.joss.20-0758
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