We have located links that may give you full text access.
Development of three-dimensional facial expression models using morphing methods for fabricating facial prostheses.
Journal of Prosthodontic Research 2018 September 14
PURPOSE: It is essential to fabricate a best-fit three-dimensional (3D) facial prosthesis model capable of facial expressions. In order for the facial prosthesis to remain in position, especially around marginal areas subject to movement, a new method of making 3D facial expression models using time-series data allowing changes in facial expression by morphing technique was developed.
METHODS: Seven normal subjects and seven patients with nasal defects or nasal deformities participated in this study. Three distinct facial expressions (i.e., a neutral expression, smiled, and open mouthed) were digitally acquired with a facial scanner. Prepared template models were transformed to homologous models, which can represent the form as shape data with the same number of point cloud data of the same topology referring to the scanning data. Finally, 3D facial expression models were completed by generating a morphing image based on two sets of homologous models, and the accuracy of the homologous models of all subjects was evaluated.
RESULTS: 3D facial expression models of both normal subjects and patients with nasal defects were successfully generated. No significant differences in shape between the scanned models and homologous models were shown.
CONCLUSIONS: The high accuracy of this 3D facial expression model in both normal subjects and patients suggests its use for fabricating facial prostheses.
METHODS: Seven normal subjects and seven patients with nasal defects or nasal deformities participated in this study. Three distinct facial expressions (i.e., a neutral expression, smiled, and open mouthed) were digitally acquired with a facial scanner. Prepared template models were transformed to homologous models, which can represent the form as shape data with the same number of point cloud data of the same topology referring to the scanning data. Finally, 3D facial expression models were completed by generating a morphing image based on two sets of homologous models, and the accuracy of the homologous models of all subjects was evaluated.
RESULTS: 3D facial expression models of both normal subjects and patients with nasal defects were successfully generated. No significant differences in shape between the scanned models and homologous models were shown.
CONCLUSIONS: The high accuracy of this 3D facial expression model in both normal subjects and patients suggests its use for fabricating facial prostheses.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app