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Automatically Generating Subject-specific Functional Tooth Surfaces Using Virtual Mastication

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Abstract

High-accuracy geometrical models of a subject’s mandibular and maxillary teeth are combined with recordings of natural chewing trajectories of the same subject to obtain a subject-specific virtual model of mastication—the virtual masticator. The virtual masticator and a shape-optimization algorithm, which is based on removing collisions occurring between a generic maxillary tooth/teeth and the mandibular antagonists during mastication, is used to automatically reconstruct functional tooth surfaces. The process was tested using a chewing trajectory stemming from recordings made of an individual while eating elastic-type foods, a generic maxillary tooth, and the mandibular second molar of that individual. Comparing the obtained results with the actual tooth, the errors within the occlusal and functional regions of the the right second maxillary molar range between −90 and 200 μm and these errors do not change any more after three chewing cycles. These results indicate that a small number of chewing cycles is sufficient to remove occlusal interferences in the virtual tooth model. Such automatically reconstructed tooth surfaces can provide guidance during the design stage of dental fixed restorations manufactured using computer-aided design and manufacturing (CAD/CAM) systems and provide additional information for the design of dental implants or bridges.

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Acknowledgment

This work was funded through the Foundation for Research in Science and Technology (FRST) under Contract Number UOAX0406. The author O.R. would also like to thank the German Research Foundation (DFG) for financial support of the project within the Cluster of Excellence in Simulation Technology (EXC 310/1) at the University of Stuttgart.

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Authors and Affiliations

  1. Bioengineering Institute, The University of Auckland, Private Bag 92019, Auckland 1, New Zealand

    H. Saini & A. J. Pullan

  2. The Department of Engineering Science, Faculty of Engineering, The University of Auckland, Private Bag 92019, Auckland 1, New Zealand

    A. J. Pullan

  3. Department of Oral Rehabilitation, Faculty of Dentistry, University of Otago, P.O. Box 647, Dunedin, New Zealand

    J. N. Wadell

  4. SRC Simulation Technology, Universität Stuttgart, Pfaffenwaldring 7a, 70569, Stuttgart, Germany

    Oliver Röhrle

Authors
  1. H. Saini
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  2. J. N. Wadell
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  3. A. J. Pullan
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  4. Oliver Röhrle
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Correspondence to Oliver Röhrle.

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Saini, H., Wadell, J.N., Pullan, A.J. et al. Automatically Generating Subject-specific Functional Tooth Surfaces Using Virtual Mastication. Ann Biomed Eng 37, 1646–1653 (2009). https://doi.org/10.1007/s10439-009-9725-y

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  • DOI: https://doi.org/10.1007/s10439-009-9725-y

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