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首页> 外文期刊>Medical image analysis >Skuller: A volumetric shape registration algorithm for modeling skull deformities
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Skuller: A volumetric shape registration algorithm for modeling skull deformities

机译：Skuller：用于建模头骨变形的体积形状配准算法

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摘要

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. (C) 2015 Elsevier B.V. All rights reserved.
机译：我们提出一种用于3D实体形状的体积配准的算法。与以前基于图像的配准相比，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，我们的方法可以更好地捕获数据的体积性质，例如骨骼厚度。我们将我们的算法应用于研究由特定状况（即颅骨前突）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：四面体网格和由从计算机断层扫描（CT）扫描中分割出来的一组体素单元表示的体素化对象。我们的通用框架首先执行全局配准，然后启动一个新颖的弹性配准过程，该过程使用尽可能多的体积信息，同时将健康人头骨的通用模板四面体网格朝体素细胞的基本几何形状变形。两种数据都是高分辨率的，并且因大的非刚性变形而不同。与重建和医学图像配准领域中的最新技术相比，我们的全自动解决方案快速准确。我们使用所得配准来匹配从医学数据中提取的地面真相表面，并量化解剖畸形的严重程度。 （C）2015 Elsevier B.V.保留所有权利。

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