Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications

Auto-detection of arch curve from dental meshes

Authors
Ting Wu, Libing Zhang
Corresponding Author
Ting Wu
Available Online January 2017.
DOI
10.2991/icmmita-16.2016.265How to use a DOI?
Keywords
dental arch; triangular meshes; feature extraction; skeleton line; B-spline fitting
Abstract

Building the form of dental arch is of great importance for orthodontic diagnosis and treatment. This paper presents a novel automated method for detecting the arch curve from dental triangular meshes with minimal user intervention. The feature region between gingiva and teeth were firstly extracted based on discrete curvature analysis. Then using the feature region as reference, a feature image were generated where the arch skeleton is detected. The arch curve were finally computed to approximate the skeleton line based on B-spline extended fitting. The experiment results demonstrate that the method is fast and robust even in the presence of malocclusion.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
Series
Advances in Computer Science Research
Publication Date
January 2017
ISBN
10.2991/icmmita-16.2016.265
ISSN
2352-538X
DOI
10.2991/icmmita-16.2016.265How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Ting Wu
AU  - Libing Zhang
PY  - 2017/01
DA  - 2017/01
TI  - Auto-detection of arch curve from dental meshes
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 1136
EP  - 1140
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.265
DO  - 10.2991/icmmita-16.2016.265
ID  - Wu2017/01
ER  -