Automatic virtual alignment of dental arches in orthodontics

AbstractA key task in orthodontic treatment planning is to align the teeth in a given lower and upper arch so as to establish an ideal occlusion (i.e., contact relationship), subject to certain dental constraints. A simulation- based approach is introduced to establish a near- optimal occlusion based on certain dental constraints that are defined using features on tooth surfaces (e.g., cusps, ridges, incisal edges etc.). The alignment process is modeled as the simulation of a hypothetical spring- mass system where masses representing teeth are connected and influenced by springs representing dental constraints. The set of constraints chosen is based on well- known guidelines to achieve normal occlusion and to detect the most common type of orthodontic errors. The design and implementation of such a simulation- based system are discussed and experimental results are provided to demonstrate the efficacy of the approach.

[1]  Julian B. Woelfel,et al.  Dental Anatomy: Its Relevance to Dentistry , 1990 .

[2]  D. Logan A First Course in the Finite Element Method , 2001 .

[3]  Kamran Iqbal,et al.  Collision detection: A survey , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

[4]  David Baraff Physically Based Modeling Implicit Methods for Differential Equations , 2001 .

[5]  Carme Torras,et al.  3D collision detection: a survey , 2001, Comput. Graph..

[6]  Sim Heng Ong,et al.  Optimal occlusion of teeth using planar structure information , 2010, Machine Vision and Applications.

[7]  Ravi Janardan,et al.  Automatic Feature Identification in Dental Meshes , 2012 .

[8]  Ravi Janardan,et al.  Improved Segmentation of Teeth in Dental Models , 2011 .

[9]  Xiaobo Zhou,et al.  An Automatic and Robust Algorithm of Reestablishment of Digital Dental Occlusion , 2010, IEEE Transactions on Medical Imaging.

[10]  Sverre J. Aarseth Gravitational N-Body Simulations: Tools and Algorithms , 2003 .

[11]  E. L. Gottlieb Grading your orthodontic treatment results. , 1975, Journal of clinical orthodontics : JCO.

[12]  Ming C. Lin,et al.  Collision Detection between Geometric Models: A Survey , 1998 .

[13]  Gottlieb El Grading your orthodontic treatment results. , 1975 .

[14]  S. E. Owens,et al.  Objective grading system for dental casts and panoramic radiographs. American Board of Orthodontics. , 1998, American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics.

[15]  Sverre J. Aarseth,et al.  Gravitational N-Body Simulations , 2003 .

[16]  Thomas Kronfeld,et al.  Snake-Based Segmentation of Teeth from Virtual Dental Casts , 2010 .

[17]  L. Andrews The six keys to normal occlusion. , 1972, American journal of orthodontics.