Lateral facial soft-tissue prediction model: analysis using Fourier shape descriptors and traditional cephalometric methods.

Abstract:

:This study was designed to investigate the relationship between traditional skeletal cephalometric measurement and Fourier analysis of the lateral soft-tissue profile. A random sample of 121 untreated subjects of European descent, with wide ranges of malocclusions and underlying facial patterns, was selected in the Orthodontic Unit at the University of Melbourne. Lateral cephalograms were available for all subjects. Both traditional lateral cephalometric analysis and Fourier soft-tissue profile analysis were carried out. Multivariate statistical analysis among 11 hard-tissue cephalometric measurements and the first 50 Fourier harmonics was then performed. This analysis formed the basis for a subsequently proposed soft-tissue prediction model. From this model, 50 predicted x- and y-harmonics were generated for each subject in the total sample. Calculation of Pearson's correlation coefficients between the actual and predicted harmonics revealed strong relationships for many of the lower-order harmonics. To further test the model, the prediction-coefficients derived from all 121 subjects were then used to make predictions for the first 50 x- and y-harmonics for a subgroup of 10 independent test subjects. Once again, Pearson's correlations between the actual and predicted harmonics of the test model in the lower-order harmonics revealed strong associations. Superimposition of the actual and predicted soft-tissue outlines, however, revealed that much actual detail in the region between the nose and the chin was still lost using the predicted Fourier harmonics. This suggests that soft-tissue prediction based on this Fourier test model, while already useful in Forensic facial reconstruction, may not yet be appropriate for useful diagnosis and planning in clinical disciplines.

journal_name

Am J Phys Anthropol

authors

Rose AD,Woods MG,Clement JG,Thomas CD

doi

10.1002/ajpa.10173

subject

Has Abstract

pub_date

2003-06-01 00:00:00

pages

172-80

issue

2

eissn

0002-9483

issn

1096-8644

journal_volume

121

pub_type

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