基于无边界约束生物力学模型的肝脏术中变形矫正表面匹配

Zixin Yang;Richard Simon;Kelly Merrell;Cristian A. Linte
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引用次数: 0

摘要

在图像引导的肝脏手术中,3D-3D非刚性配准方法在估计术前模型与以点云表示的术中表面之间的映射,解决组织变形的挑战方面起着至关重要的作用。通常,这些方法将以有限元模型(FEM)表示的生物力学模型纳入应变能项,以正则化表面匹配项。提出了一种3D-3D非刚性配准方法,该方法在曲面匹配项中引入了改进的有限元方法。修正后的有限元法通过修改有限元法的刚度矩阵和采用对角加载进行稳定,从而减少了对边界条件的要求。因此,修正后的曲面匹配项不需要指定边界条件,也不需要额外的应变能项来规范曲面匹配项。优化是通过加速梯度算法实现的,进一步增强了我们提出的方法来确定最优步长。我们评估了我们的方法,并将其与不同数据集的几种最先进的方法进行了比较。我们的直接和有效的方法始终优于或达到了与最先进的方法相当的性能。我们的代码和数据集可在https://github.com/zixinyang9109/BCF-FEM上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Boundary Constraint-Free Biomechanical Model-Based Surface Matching for Intraoperative Liver Deformation Correction
In image-guided liver surgery, 3D-3D non-rigid registration methods play a crucial role in estimating the mapping between the preoperative model and the intraoperative surface represented as point clouds, addressing the challenge of tissue deformation. Typically, these methods incorporate a biomechanical model, represented as a finite element model (FEM), into the strain energy term to regularize a surface matching term. We propose a 3D-3D non-rigid registration method that incorporates a modified FEM into the surface matching term. The modified FEM alleviates the need to specify boundary conditions, which is achieved by modifying the stiffness matrix of a FEM and using diagonal loading for stabilization. As a result, the modified surface matching term does not require the specification of boundary conditions or an additional strain energy term to regularize the surface matching term. Optimization is achieved through an accelerated gradient algorithm, further enhanced by our proposed method for determining the optimal step size. We evaluated our method and compared it to several state-of-the-art methods across various datasets. Our straightforward and effective approach consistently outperformed or achieved comparable performance to the state-of-the-art methods. Our code and datasets are available at https://github.com/zixinyang9109/BCF-FEM.
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