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Talairach-Tournoux brain atlas registration using a metalforming principle-based finite element method.

机译:Talairach-Tournoux脑图谱注册使用基于金属成形原理的有限元方法。

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In this paper, a novel non-rigid registration method is proposed for registration of the Talairach-Tournoux brain atlas with MRI images and the Schaltenbrand-Wahren brain atlas. A metalforming principle-based finite element method with the large deformation problem is used to find the local deformation, in which finite element equations are governed by constraints in the form of displacements derived from the correspondence relationship between extracted feature points. Some detectable substructures, such as the cortical surface, ventricles and corpus callosum, are first extracted from MRI, forming feature points which are classified into different groups. The softassign method is used to establish the correspondence relationship between feature points within each group and to obtain the global transformation concurrently. The displacement constraints are then derived from the correspondence relationship. A metalforming principle-based finite element method with the large deformation problem is used in which finite element equations are reorganized and simplified by integrating the displacement constraints into the system equations. Our method not only matches the model to the data efficiently, but also decreases the degrees of freedom of the system and consequently reduces the computational cost. The method is illustrated by matching the Talairach-Tournoux brain atlas to MRI normal and pathological data and to the Schaltenbrand-Wahren brain atlas. We compare the results quantitatively between the force assignment-based method and the proposed method. The results show that the proposed method yields more accurate results in a fraction of the time taken by the previous method.
机译:在本文中,提出了一种新颖的非刚性配准方法,用于通过MRI图像和Schaltenbrand-Wahren脑图谱对Talairach-Tournoux脑图谱进行配准。使用具有大变形问题的基于金属成形原理的有限元方法来查找局部变形,在该局部变形中,有限元方程由约束条件控制,这些约束条件是根据提取的特征点之间的对应关系得出的位移形式。首先从MRI中提取一些可检测的子结构,例如皮质表面,心室和call体,形成特征点,将其分类为不同的组。软分配方法用于建立每个组内特征点之间的对应关系,并同时获得全局变换。然后从对应关系中得出位移约束。使用具有大变形问题的基于金属成形原理的有限元方法,其中通过将位移约束整合到系统方程中来重组和简化有限元方程。我们的方法不仅有效地使模型与数据匹配,而且降低了系统的自由度,从而降低了计算成本。通过将Talairach-Tournoux脑图谱与MRI正常和病理数据以及Schaltenbrand-Wahren脑图谱进行匹配来说明该方法。我们定量地比较了基于力分配的方法和所提出的方法的结果。结果表明,所提出的方法在前一种方法所花费的时间的一小部分内产生了更准确的结果。

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