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Three-dimensional models of craniofacial variation over the generalpopulation are useful for assessing pre- and post-operative head shape whentreating various craniofacial conditions, such as craniosynostosis. We presenta new method of automatically building both sagittal profile models and full 3Dsurface models of the human head using a range of techniques in 3D surfaceimage analysis; in particular, automatic facial landmarking using supervisedmachine learning, global and local symmetry plane detection using a variant oftrimmed iterative closest points, locally-affine template warping (for full 3Dmodels) and a novel pose normalisation using robust iterative ellipse fitting.The PCA-based models built using the new pose normalisation are more compactthan those using Generalised Procrustes Analysis and we demonstrate theirutility in a clinical case study.

Automatic 3D modelling of craniofacial form