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Med Biol Eng Comput. 2017 Sep;55(9):1635-1647. doi: 10.1007/s11517-017-1626-x. Epub 2017 Feb 7.

Deformation of facial model for complete denture prosthesis using ARAP group method and elastic properties.

Author information

1
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, 29 Yudao Street, Qinhuai Dist, Nanjing, 210016, People's Republic of China.
2
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, 29 Yudao Street, Qinhuai Dist, Nanjing, 210016, People's Republic of China. dai_ning@nuaa.edu.cn.
3
Research Centre of Engineering and Technology for Computerized Dentistry, Ministry of Health, Peking University School and Hospital of Stomatology, Beijing, 100081, People's Republic of China. polarshining@163.com.
4
Research Centre of Engineering and Technology for Computerized Dentistry, Ministry of Health, Peking University School and Hospital of Stomatology, Beijing, 100081, People's Republic of China.

Abstract

With the development of 3D printing and computer graphics technology, mouth rehabilitation has increasingly adopted digital methods. This research proposes a new method to transform the appearance of facial model after complete denture prosthesis. A feature template with few feature points is first constructed according to the facial muscle anatomy and facial deformation after complete denture prosthesis. Next, the traditional as-rigid-as-possible (ARAP) method is optimised by clustering based on facial muscles. The optimised ARAP method is then used for real-time and interactive simulations. Finally, by classifying the degrees of elasticity in the model with additional weights, the simulation can be customised to the skin of individual patients. Different degrees of elastic deformation and post-operative models are superimposed for match analysis. Compared with our previous study, the error is reduced by 24.05%. Results show that our method can deform facial models accurately and efficiently.

KEYWORDS:

Complete denture; Feature classification; Mesh editing; Nonlinear method; Soft tissue simulation

PMID:
28176265
DOI:
10.1007/s11517-017-1626-x
[Indexed for MEDLINE]

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