Abstract
Contemporary cephalometric imaging in dental orthodontic treatment uses anatomical features on X-ray images for analysis; however, the available features are limited. The mandible, for example, has a simple structure compared to that of the maxilla, and all the analytical features are distributed on the outer edge. The aims of this study are to simulate the growth process of the mandible based on the relevant orthodontic surveys and through a finite element analysis using ANSYS software, to calculate the optimum growth parameters using genetic algorithms, and to establish new features in the absence of anatomical structure. This study proposes a calculation method for establishing new features, and provides more comprehensive information for pretreatment diagnosis in orthodontics.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2011 IEEE International Conference on Granular Computing, GrC 2011 |
| Pages | 551-555 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2011 |
| Event | 2011 IEEE International Conference on Granular Computing, GrC 2011 - Kaohsiung, Taiwan Duration: Nov 8 2011 → Nov 10 2011 |
Other
| Other | 2011 IEEE International Conference on Granular Computing, GrC 2011 |
|---|---|
| Country | Taiwan |
| City | Kaohsiung |
| Period | 11/8/11 → 11/10/11 |
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Keywords
- finite element
- genetic algorithm
- orthodontic landmarks
ASJC Scopus subject areas
- Software
Cite this
Generation of historical mandible landmarks for orthodontic treatment using genetic algorithm and finite element method. / Pao, Yu Lun; Liu, Thomas Jin Chee; Wong, Jau Min; Chiang, I. Jen.
Proceedings - 2011 IEEE International Conference on Granular Computing, GrC 2011. 2011. p. 551-555 6122656.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Generation of historical mandible landmarks for orthodontic treatment using genetic algorithm and finite element method
AU - Pao, Yu Lun
AU - Liu, Thomas Jin Chee
AU - Wong, Jau Min
AU - Chiang, I. Jen
PY - 2011
Y1 - 2011
N2 - Contemporary cephalometric imaging in dental orthodontic treatment uses anatomical features on X-ray images for analysis; however, the available features are limited. The mandible, for example, has a simple structure compared to that of the maxilla, and all the analytical features are distributed on the outer edge. The aims of this study are to simulate the growth process of the mandible based on the relevant orthodontic surveys and through a finite element analysis using ANSYS software, to calculate the optimum growth parameters using genetic algorithms, and to establish new features in the absence of anatomical structure. This study proposes a calculation method for establishing new features, and provides more comprehensive information for pretreatment diagnosis in orthodontics.
AB - Contemporary cephalometric imaging in dental orthodontic treatment uses anatomical features on X-ray images for analysis; however, the available features are limited. The mandible, for example, has a simple structure compared to that of the maxilla, and all the analytical features are distributed on the outer edge. The aims of this study are to simulate the growth process of the mandible based on the relevant orthodontic surveys and through a finite element analysis using ANSYS software, to calculate the optimum growth parameters using genetic algorithms, and to establish new features in the absence of anatomical structure. This study proposes a calculation method for establishing new features, and provides more comprehensive information for pretreatment diagnosis in orthodontics.
KW - finite element
KW - genetic algorithm
KW - orthodontic landmarks
UR - http://www.scopus.com/inward/record.url?scp=84856791785&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84856791785&partnerID=8YFLogxK
U2 - 10.1109/GRC.2011.6122656
DO - 10.1109/GRC.2011.6122656
M3 - Conference contribution
SN - 9781457703713
SP - 551
EP - 555
BT - Proceedings - 2011 IEEE International Conference on Granular Computing, GrC 2011
ER -