Three-dimensional tooth model reconstruction based on fusion of dental computed tomography images and laser-scanned images_Journal of Biomedical Engineering

Authors：

ZHANG Dongxia ^1,2 , GAN Yangzhou ^1,2 , XIONG Jing ¹ ,  XIA Zeyang ^1,2

1. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055 P.R.China;
2. CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Shenzhen, Guangdong 518055 P.R.China;

Corresponding author：

XIA Zeyang, Email: zy.xia@siat.ac.cn

Keywords：

orthodontics; three-dimensional tooth model; registration; fusion; reconstruction

DOI：

10.7507/1001-5515.201604014

Video：

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Complete three-dimensional (3D) tooth model provides essential information to assist orthodontists for diagnosis and treatment planning. Currently, 3D tooth model is mainly obtained by segmentation and reconstruction from dental computed tomography (CT) images. However, the accuracy of 3D tooth model reconstructed from dental CT images is low and not applicable for invisalign design. And another serious problem also occurs,i.e. frequentative dental CT scan during different intervals of orthodontic treatment often leads to radiation to the patients. Hence, this paper proposed a method to reconstruct tooth model based on fusion of dental CT images and laser-scanned images. A complete 3D tooth model was reconstructed with the registration and fusion between the root reconstructed from dental CT images and the crown reconstructed from laser-scanned images. The crown of the complete 3D tooth model reconstructed with the proposed method has higher accuracy. Moreover, in order to reconstruct complete 3D tooth model of each orthodontic treatment interval, only one pre-treatment CT scan is needed and in the orthodontic treatment process only the laser-scan is required. Therefore, radiation to the patients can be reduced significantly.

Citation： ZHANG Dongxia, GAN Yangzhou, XIONG Jing, XIA Zeyang. Three-dimensional tooth model reconstruction based on fusion of dental computed tomography images and laser-scanned images. Journal of Biomedical Engineering, 2017, 34(1): 7-14. doi: 10.7507/1001-5515.201604014 Copy

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2.	齐小秋. 第三次全国口腔健康流行病学调查报告. 北京: 人民卫生出版社, 2008: 1-276.
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4.	刘枭雄, 石峰, 张继武. 基于三角网格演化的 CBCT 牙齿图像分割方法. 中国医疗器械杂志, 2011, 35(6): 414-417.
5.	马亚奇, 李忠科, 王先泽. 基于测地路径的牙齿模型交互分割算法研究. 中国图象图形学报, 2011, 16(4): 554-558.
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7.	Boyd R L, Miller R J, Vlasklic V. The invisalign system in adult orthodontics:Mild crowding and space closure cases. J Clin Orthod, 2000, 34(4): 203-212.
8.	Gan Yangzhou, Xia Zeyang, Xiong Jing, et al. Toward accurate tooth segmentation from computed tomography images using a hybrid level set model. Med Phys, 2015, 42(1): 14-27.
9.	Xia Zeyang, Gan Yangzhou, Xiong Jing, et al. Crown segmentation from computed tomography images with metal artifacts. IEEE Signal Process Lett, 2016, 23(5): 678-682.
10.	de Waard O, Rangel F A, Fudalej P S, et al. Reproducibility and accuracy of linear measurements on dental models derived from cone-beam computed tomography compared with digital dental casts. Am J Orthod Dentofacial Orthop, 2014, 146(3): 328-336.
11.	Lorensen W E, Cline H E. Marching cubes:a high resolution 3d surface construction algorithm. Comput Graphics, 1987, 21(4): 163-169.
12.	李成军, 张弛, 汪国平. 交互标记控制的快速网格分割. 北京大学学报:自然科学版, 2006, 42(5): 662-667.
13.	Adams R, Bischof L. Seeded region growing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1994, 16(6): 641-647.
14.	Jolliffe I T. Principal component analysis. 2nd ed. New York: Springer, 2002: 1-488.
15.	Besl P J, Mckay N D. A method for registration of 3-D shapes. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 1992, 14(2): 239-256.
16.	Wald I, Havran V. On building fast kd-Trees for Ray Tracing,and on doing that in O(N log N)//IEEE Symposium on Interactive Ray Tracing IEEE Computer Society, Salt Lake City, 2006: 61-69.
17.	Kuo C C, Yau H T. A delaunay-based region-growing approach to surface Reconstruction from unorganized points. Comput Aided Des, 2005, 37(8): 825-835.
18.	Kim B C, Lee C E, Park W, et al. Integration accuracy of digital dental models and 3-dimensional computerized tomography images by sequential point- and surface-based markerless registration. Oral Surg Oral Med Oral Pathol Oral Radiol Endod, 2010, 110(3): 370-378.
19.	Ye Niansong, Long Hu, Xue J, et al. Integration accuracy of laser-scanned dental models into maxillofacial cone beam computed tomography images of different voxel sizes with different segmentation threshold settings. Oral Surg Oral Med Oral Pathol Oral Radiol Endod, 2014, 117(6): 780-786.

1. 傅民魁. 口腔正畸学. 北京: 人民卫生出版社, 2008: 1-317.
2. 齐小秋. 第三次全国口腔健康流行病学调查报告. 北京: 人民卫生出版社, 2008: 1-276.
3. Kondo T, Ong S H, Foong K W. Tooth segmentation of dental study models using range images. IEEE Trans Med Imaging, 2004, 23(3): 350-362.
4. 刘枭雄, 石峰, 张继武. 基于三角网格演化的 CBCT 牙齿图像分割方法. 中国医疗器械杂志, 2011, 35(6): 414-417.
5. 马亚奇, 李忠科, 王先泽. 基于测地路径的牙齿模型交互分割算法研究. 中国图象图形学报, 2011, 16(4): 554-558.
6. Kuncio D, Maganzini A, Shelton C, et al. Invisalign and traditional orthodontic treatment postretention outcomes compared using the American Board of Orthodontics Objective Grading System. Angle Orthod, 2007, 77(5): 864-869.
7. Boyd R L, Miller R J, Vlasklic V. The invisalign system in adult orthodontics:Mild crowding and space closure cases. J Clin Orthod, 2000, 34(4): 203-212.
8. Gan Yangzhou, Xia Zeyang, Xiong Jing, et al. Toward accurate tooth segmentation from computed tomography images using a hybrid level set model. Med Phys, 2015, 42(1): 14-27.
9. Xia Zeyang, Gan Yangzhou, Xiong Jing, et al. Crown segmentation from computed tomography images with metal artifacts. IEEE Signal Process Lett, 2016, 23(5): 678-682.
10. de Waard O, Rangel F A, Fudalej P S, et al. Reproducibility and accuracy of linear measurements on dental models derived from cone-beam computed tomography compared with digital dental casts. Am J Orthod Dentofacial Orthop, 2014, 146(3): 328-336.
11. Lorensen W E, Cline H E. Marching cubes:a high resolution 3d surface construction algorithm. Comput Graphics, 1987, 21(4): 163-169.
12. 李成军, 张弛, 汪国平. 交互标记控制的快速网格分割. 北京大学学报:自然科学版, 2006, 42(5): 662-667.
13. Adams R, Bischof L. Seeded region growing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1994, 16(6): 641-647.
14. Jolliffe I T. Principal component analysis. 2nd ed. New York: Springer, 2002: 1-488.
15. Besl P J, Mckay N D. A method for registration of 3-D shapes. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 1992, 14(2): 239-256.
16. Wald I, Havran V. On building fast kd-Trees for Ray Tracing,and on doing that in O(N log N)//IEEE Symposium on Interactive Ray Tracing IEEE Computer Society, Salt Lake City, 2006: 61-69.
17. Kuo C C, Yau H T. A delaunay-based region-growing approach to surface Reconstruction from unorganized points. Comput Aided Des, 2005, 37(8): 825-835.
18. Kim B C, Lee C E, Park W, et al. Integration accuracy of digital dental models and 3-dimensional computerized tomography images by sequential point- and surface-based markerless registration. Oral Surg Oral Med Oral Pathol Oral Radiol Endod, 2010, 110(3): 370-378.
19. Ye Niansong, Long Hu, Xue J, et al. Integration accuracy of laser-scanned dental models into maxillofacial cone beam computed tomography images of different voxel sizes with different segmentation threshold settings. Oral Surg Oral Med Oral Pathol Oral Radiol Endod, 2014, 117(6): 780-786.

Journal of Biomedical Engineering

Three-dimensional tooth model reconstruction based on fusion of dental computed tomography images and laser-scanned images

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