Automated digital dental articulation

  • Authors:
  • James J. Xia;Yu-Bing Chang;Jaime Gateno;Zixiang Xiong;Xiaobo Zhou

  • Affiliations:
  • The Methodist Hospital Research Institute, Houston, Texas;The Methodist Hospital Research Institute, Houston, Texas and Texas A&M University, College Station, Texas;The Methodist Hospital Research Institute, Houston, Texas;Texas A&M University, College Station, Texas;The Methodist Hospital Research Institute, Houston, Texas

  • Venue:
  • MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
  • Year:
  • 2010

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Abstract

Articulating digital dental models is often inaccurate and very time-consuming. This paper presents an automated approach to efficiently articulate digital dental models to maximum intercuspation (MI). There are two steps in our method. The first step is to position the models to an initial position based on dental curves and a point matching algorithm. The second step is to finally position the models to the MI position based on our novel approach of using iterative surface-based minimum distance mapping with collision constraints. Finally, our method was validated using 12 sets of digital dental models. The results showed that using our method the digital dental models can be accurately and effectively articulated to MI position.