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Abstract
We present a fully-automatic image processing pipeline to build a set of 2D morphable models of three craniofacial profiles from orthogonal viewpoints, side view, front view and top view, using 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 profiles from 3D raw scans. 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 models and the profile dataset used to construct it.
Highlights
In the medical analysis of craniofacial shape, the visualisation of 2D profiles [1] is highly informative when looking for deviations from population norms
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
Contributions: We propose a new pipeline to build a 2D morphable model of the craniofacial sagittal profile and augment it with profile models from frontal and top down views
Summary
In the medical analysis of craniofacial shape, the visualisation of 2D profiles [1] is highly informative when looking for deviations from population norms. A morphable model is constructed by performing some form of dimensionality reduction, typically Principal Component Analysis (PCA), on a training dataset of shape examples. This is feasible only if each shape is first re-parametrised into a consistent form where the number of points and their anatomical locations are made consistent to some level of accuracy.
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