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使用薄板样条变换和柱面投影的三维颅面配准

3D craniofacial registration using thin-plate spline transform and cylindrical surface projection.

作者信息

Chen Yucong, Zhao Junli, Deng Qingqiong, Duan Fuqing

机构信息

College of Information Science and Technology, Beijing Normal University, Beijing, China.

School of Data Science and Software Engineering, Qingdao University, Qingdao, China.

出版信息

PLoS One. 2017 Oct 5;12(10):e0185567. doi: 10.1371/journal.pone.0185567. eCollection 2017.

Abstract

Craniofacial registration is used to establish the point-to-point correspondence in a unified coordinate system among human craniofacial models. It is the foundation of craniofacial reconstruction and other craniofacial statistical analysis research. In this paper, a non-rigid 3D craniofacial registration method using thin-plate spline transform and cylindrical surface projection is proposed. First, the gradient descent optimization is utilized to improve a cylindrical surface fitting (CSF) for the reference craniofacial model. Second, the thin-plate spline transform (TPST) is applied to deform a target craniofacial model to the reference model. Finally, the cylindrical surface projection (CSP) is used to derive the point correspondence between the reference and deformed target models. To accelerate the procedure, the iterative closest point ICP algorithm is used to obtain a rough correspondence, which can provide a possible intersection area of the CSP. Finally, the inverse TPST is used to map the obtained corresponding points from the deformed target craniofacial model to the original model, and it can be realized directly by the correspondence between the original target model and the deformed target model. Three types of registration, namely, reflexive, involutive and transitive registration, are carried out to verify the effectiveness of the proposed craniofacial registration algorithm. Comparison with the methods in the literature shows that the proposed method is more accurate.

摘要

颅面配准用于在人类颅面模型的统一坐标系中建立点对点对应关系。它是颅面重建和其他颅面统计分析研究的基础。本文提出了一种基于薄板样条变换和柱面投影的非刚性三维颅面配准方法。首先,利用梯度下降优化改进参考颅面模型的柱面拟合(CSF)。其次,应用薄板样条变换(TPST)将目标颅面模型变形为参考模型。最后,使用柱面投影(CSP)来推导参考模型和变形目标模型之间的点对应关系。为了加速该过程,使用迭代最近点ICP算法获得粗略对应关系,这可以提供CSP的可能相交区域。最后,使用逆TPST将从变形目标颅面模型获得的对应点映射到原始模型,并且可以通过原始目标模型与变形目标模型之间的对应关系直接实现。进行了三种类型的配准,即自反配准、对合配准和传递配准,以验证所提出的颅面配准算法的有效性。与文献中的方法比较表明,所提出的方法更准确。

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