Skuller: A volumetric shape registration algorithm for modeling skull deformities
Skuller: A volumetric shape registration algorithm for modeling skull deformities
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DOI：
10.1016/j.media.2015.03.005
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发表时间：
2015-07
影响因子：
10.9
通讯作者：
Y. Sahillioğlu;L. Kavan
中科院分区：
文献类型：
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作者：
Y. Sahillioğlu;L. Kavan
我们提出了一种 3D 实体形状的体积配准算法。与之前基于图像的配准工作相比，我们的技术通过利用模板四面体网格实现了更高的效率。与基于点和基于表面的配准技术相比，我们的方法更好地捕获数据的体积性质，例如骨骼厚度。我们应用我们的算法来研究由特定情况（即颅缝早闭）引起的病理性颅骨畸形。我们系统的输入是一对体积 3D 形状：一个四面体网格和一个体素化对象，该体素化对象由一组从计算机断层扫描 (CT) 扫描中分割出来的体素单元表示。我们的总体框架首先执行全局配准，然后启动一种新颖的弹性配准过程，该过程使用尽可能多的体积信息，同时将健康人类头骨的通用模板四面体网格变形为体素细胞的基础几何形状。两种数据都是高分辨率的，并且存在较大的非刚性变形。与重建和医学图像配准领域的最先进技术相比，我们的全自动解决方案快速且准确。我们使用所得配准来匹配从医学数据中提取的地面实况表面，并量化解剖畸形的严重程度。
We present an algorithm for volumetric registration of 3D solid shapes. In comparison to previous work on image based registration, our technique achieves higher efficiency by leveraging a template tetrahedral mesh. In contrast to point- and surface-based registration techniques, our method better captures volumetric nature of the data, such as bone thickness. We apply our algorithm to study pathological skull deformities caused by a particular condition, i.e., craniosynostosis. The input to our system is a pair of volumetric 3D shapes: a tetrahedral mesh and a voxelized object represented by a set of voxel cells segmented from computed tomography (CT) scans. Our general framework first performs a global registration and then launches a novel elastic registration process that uses as much volumetric information as possible while deforming the generic template tetrahedral mesh of a healthy human skull towards the underlying geometry of the voxel cells. Both data are high-resolution and differ by large non-rigid deformations. Our fully-automatic solution is fast and accurate, as compared with the state of the arts from the reconstruction and medical image registration fields. We use the resulting registration to match the ground-truth surfaces extracted from the medical data as well as to quantify the severity of the anatomical deformity.