Chakravarty, M. Mallar, Aleong, Rosanne, Leonard, Gabriel, Perron, Michel, Pike, G. Bruce, Richer, Louis, Veillette, Suzanne, Pausova, Zdenka et Paus, Tomáš. (2011). Automated analysis of craniofacial morphology using magnetic resonance images. PLoS ONE, 6, (5),
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URL officielle: http://journals.plos.org/plosone/article?id=10.137...
Résumé
Quantitative analysis of craniofacial morphology is of interest to scholars working in a wide variety of disciplines, such as anthropology, developmental biology, and medicine. T1-weighted (anatomical) magnetic resonance images (MRI) provide excellent contrast between soft tissues. Given its three-dimensional nature, MRI represents an ideal imaging modality for the analysis of craniofacial structure in living individuals. Here we describe how T1-weighted MR images, acquired to examine brain anatomy, can also be used to analyze facial features. Using a sample of typically developing adolescents from the Saguenay Youth Study (N = 597; 292 male, 305 female, ages: 12 to 18 years), we quantified inter-individual variations in craniofacial structure in two ways. First, we adapted existing nonlinear registration-based morphological techniques to generate iteratively a group-wise population average of craniofacial features. The nonlinear transformations were used to map the craniofacial structure of each individual to the population average. Using voxel-wise measures of expansion and contraction, we then examined the effects of sex and age on inter-individual variations in facial features. Second, we employed a landmark-based approach to quantify variations in face surfaces. This approach involves: (a) placing 56 landmarks (forehead, nose, lips, jaw-line, cheekbones, and eyes) on a surface representation of the MRI-based group average; (b) warping the landmarks to the individual faces using the inverse nonlinear transformation estimated for each person; and (3) using a principal components analysis (PCA) of the warped landmarks to identify facial features (i.e. clusters of landmarks) that vary in our sample in a correlated fashion. As with the voxel-wise analysis of the deformation fields, we examined the effects of sex and age on the PCA-derived spatial relationships between facial features. Both methods demonstrated significant sexual dimorphism in craniofacial structure in areas such as the chin, mandible, lips, and nose.
| Type de document: | Article publié dans une revue avec comité d'évaluation |
|---|---|
| Volume: | 6 |
| Numéro: | 5 |
| Version évaluée par les pairs: | Oui |
| Date: | Mai 2011 |
| Unité(s) institutionnelle(s): | Départements et unités pédagogiques > Département des sciences de la santé > Module de psychologie |
| Mots-clés: | Magnetic resonance imaging, MRI, neuroimaging, craniofacial morphology, facial analysis, imagerie par résonance magnétique, IRM, neuroimagerie, morphologie craniofaciale, analyse faciale |
| Déposé le: | 20 avr. 2016 21:56 |
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| Dernière modification: | 18 juill. 2023 19:59 |
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