Modelling of Orthogonal Craniofacial Profiles

TY - JOUR

T1 - Modelling of Orthogonal Craniofacial Profiles

AU - Dai, Hang

AU - Pears, Nicholas Edwin

AU - Duncan, Christian

N1 - © 2017 by the authors.

PY - 2017/11/30

Y1 - 2017/11/30

N2 - We present a fully-automatic image processing pipeline to build a set of 2D morphablemodels 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.

AB - We present a fully-automatic image processing pipeline to build a set of 2D morphablemodels 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.

KW - Craniofacial

KW - Craniosynostosis

KW - Morphable model

KW - Shape modelling

UR - http://www.scopus.com/inward/record.url?scp=85063940051&partnerID=8YFLogxK

U2 - 10.3390/jimaging3040055

DO - 10.3390/jimaging3040055

M3 - Article

SN - 2313-433X

VL - 3

JO - Journal of Imaging

JF - Journal of Imaging

IS - 55

M1 - 3040055

ER -