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Abstract #2444

Automated Analysis of Craniofacial Morphology using Magnetic Resonance Images

M. Mallar Chakravarty1,2, Rosanne Aleong3, Gabriel Leonard4, Michel Peron5, G. Bruce Pike4, Louis Richer6, Suzanne Veillet5, Zdenka Pausova7, Tomas Paus3,7

1Rotman Research Institute, Baycrest , Toronto, Ontario, Canada; 2Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Ontario, Canada; 3Rotman Research Institute, Baycrest, Toronto, Ontario, Canada; 4Montral Neurological Institute, McGill University, Montral, Qubec, Canada; 5CGEP de Jonquire, Jonquire, Quebec, Canada; 6Dpartement des sciences de l'ducation et de psychologie, Universit du Qubec Chicoutimi, Chicoutimi, Qubec, Canada; 7School of Psychology, University of Nottingham, Nottingham, United Kingdom

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 using voxel-based analysis and the decomposition of craniofacial features using landmark based techniques. The results demonstrate the sexual dimorphism of the human face.