Accuracy analysis of teeth 3D model based on RE Technology

DOI

10.2991/icadme-16.2016.45How to use a DOI?

Keywords

plaster dental cast model ;standard resin teeth mold model;silicone rubber material;point cloud data;Geomagic Qualify;accuracy

Abstract

At present, the silicone rubber material is the best material to turn over the plaster model. This paper was aimed to explore the error and error magnitude between the plaster model and the original one. The silicone rubber materials were used to turn over the the standard resin dental model into plaster model. A large number of point cloud data were obtained by using a hand held scanner to scan the standard resin and the turning plaster model, and the data was saved as .Stl format. The Geomagic Studio software was used to complete the processing of point cloud data, and then the boundary of the two digital dental model was extracted. Finally, comparison of the 3D and 2D was undertook by the Geomagic qualify 3D detection software, at the same time, the error analyzation was taken to text the anterior, middle, posterior segment of the dental arch, premolar and molar Pont Index. The analysis results showed that the error between gypsum model and standard resin teeth Model was 0.030 mm to 0.050 mm, although the error was very small and meet the clinical accuracy, but silicon rubber material will also affect the accuracy due to the shrinkage and other characteristics. This will lay a certain foundation for the development of oral medicine in the future.

Copyright

© 2016, 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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TY  - CONF
AU  - Dan Ma
AU  - Deqiang Zhang
AU  - Xin Li
PY  - 2017/07
DA  - 2017/07
TI  - Accuracy analysis of teeth 3D model based on RE Technology
BT  - Proceedings of the 2016 6th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2017)
PB  - Atlantis Press
SP  - 291
EP  - 296
SN  - 2352-5401
UR  - https://doi.org/10.2991/icadme-16.2016.45
DO  - 10.2991/icadme-16.2016.45
ID  - Ma2017/07
ER  -