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Automated analysis of craniofacial morphology using magnetic resonance images

Chakravarty M. Mallar, Aleong Rosanne, Leonard Gabriel, Perron Michel, Pike G. Bruce, Richer Louis, Veillette Suzanne, Pausova Zdenka et Paus Tomás. (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
Sujets:Sciences de la santé
Sciences de la santé > Sciences médicales > Neurosciences
Département, module, service et unité de recherche:Départements et modules > 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
Dernière modification:25 nov. 2016 18:22
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Creative Commons LicenseSauf indication contraire, les documents archivés dans Constellation sont rendus disponibles selon les termes de la licence Creative Commons "Paternité, pas d'utilisation commerciale, pas de modification" 2.5 Canada.

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