Automatic craniofacial registration based on radial curves. (August 2019) - Huang, Ruikun; Zhao, Junli; Duan, Fuqing; Li, Xin; Liu, Celong; Deng, Xiaodan; Pan, Zhenkuan; Wu, Zhongke; Zhou, Mingquan
Highlights: We propose a feature ponits selection method on 3D craniofacial models, which result in automatic and stable feature landmark extraction. We propose a new craniofacial registration framework using radial curves and our extracted landmarks. Our registration is automatic and effective. We perform extensive experiments on craniofacial data registration and demonstrate the effectiveness of this radial curve based registration. Graphical abstract: Abstract: Accurate registration of three-dimensional craniofacial surface is a foundation for craniofacial reconstruction. Most of craniofacial registration methods need to manually calibrate the feature points. This paper presents an automatic craniofacial registration method based on radial curves. First, we extract radial curves on both the reference and target craniofacial surfaces, and suggest an automatic feature point selection algorithms on these radial curves. Second, we align the two sets of radial curves, and develop a consistency point drift (CPD) algorithm to establish correspondences between feature points on the reference and target surfaces. Then, these feature points are used as control points of the thin plate spline transformation (TPS) algorithm, and the reference craniofacial surface is transformed toward the target craniofacial surface. Finally, the corresponding points of the reference surface on the target surface are searched to realize the registration. The experimental results show that the proposed algorithm is effective.