A 2D morphable model of craniofacial profile and its application to craniosynostosis

Abstract

We present a fully automatic image processing pipeline to build a 2D morphable model of craniofacial saggital profile from a set of 3D head surface images. Subjects in this dataset wear a close fitting latex cap to reveal the overall skull shape. Texture based 3D pose normalization and facial landmarking are applied to extract the sagittal profile from 3D raw scan. Fully automatic profile annotation, subdivision and registration methods are used to establish dense correspondence among sagittal profiles. The collection of sagittal profiles in dense correspondence are scaled and aligned using Generalised Procrustes Analysis (GPA), before applying Principal Component Analysis to generate a morphable model. Additionally, we propose a new alternative alignment called the Ellipse Centre Nasion (ECN) method. Our model is used in a case study of craniosynostosis intervention outcome evaluation and the evaluation reveals that the proposed model achieves state-of-the-art results. We make publicly available both the morphable model with matlab code and the profile dataset used to construct it.