ADRF RESEARCH REPORT
Augmentation of linear facial anthropometrics through modern morphometrics: a facial convexity example
Article first published online: 30 MAY 2011
© 2011 Australian Dental Association
Australian Dental Journal
Volume 56, Issue 2, pages 141–147, June 2011
How to Cite
Wei, R., Claes, P., Walters, M., Wholley, C. and Clement, J. (2011), Augmentation of linear facial anthropometrics through modern morphometrics: a facial convexity example. Australian Dental Journal, 56: 141–147. doi: 10.1111/j.1834-7819.2011.01315.x
- Issue published online: 30 MAY 2011
- Article first published online: 30 MAY 2011
- (Accepted for publication 26 September 2010.)
- 3-D imaging;
- property pathways
Background: The facial region has traditionally been quantified using linear anthropometrics. These are well established in dentistry, but require expertise to be used effectively. The aim of this study was to augment the utility of linear anthropometrics by applying them in conjunction with modern 3-D morphometrics.
Methods: Facial images of 75 males and 94 females aged 18–25 years with self-reported Caucasian ancestry were used. An anthropometric mask was applied to establish corresponding quasi-landmarks on the images in the dataset. A statistical face-space, encoding shape covariation, was established. The facial median plane was extracted facilitating both manual and automated indication of commonly used midline landmarks. From both indications, facial convexity angles were calculated and compared. The angles were related to the face-space using a regression based pathway enabling the visualization of facial form associated with convexity variation.
Results: Good agreement between the manual and automated angles was found (Pearson correlation: 0.9478–0.9474, Dahlberg root mean squared error: 1.15°–1.24°). The population mean angle was 166.59°–166.29° (SD 5.09°–5.2°) for males–females. The angle-pathway provided valuable feedback.
Conclusions: Linear facial anthropometrics can be extended when used in combination with a face-space derived from 3-D scans and the exploration of property pathways inferred in a statistically verifiable way.