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Non-rigid Registration with Use of Hardware-Based 3D Bezier Functions

机译:使用基于硬件的3D Bezier函数进行非刚性注册

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In this paper we introduce a new method for non-rigid voxel-based registration. In many medical applications there is a need to establish an alignment between two image datasets. Often a registration of a time-shifted medical image sequence with appearing deformation of soft tissue (e.g. pre- and intraoperative data) has to be conducted. Soft tissue deformations are usually highly non-linear. For the handling of this phenomenon and for obtaining an optimal non-linear alignment of respective datasets we transform one of them using 3D Bezier functions, which provides some inherent smoothness as well as elasticity. In order to find the optimal transformation, many evaluations of this Bezier function are necessary. In order to make the method more efficient, graphics hardware is extensively used. We applied our non-rigid algorithm successfully to MR brain images in several clinical cases and showed its value.
机译:在本文中,我们介绍了一种基于非刚性体素的注册新方法。在许多医疗应用中,需要在两个图像数据集之间建立对齐。通常必须进行时移医学图像序列的注册,该序列具有软组织的变形(例如术前和术中数据)。软组织变形通常是高度非线性的。为了处理这种现象并获得各个数据集的最佳非线性对齐,我们使用3D Bezier函数对其中之一进行了转换,该函数提供了一些固有的平滑度和弹性。为了找到最佳变换,必须对此Bezier函数进行许多评估。为了使该方法更有效,广泛使用了图形硬件。我们成功地将我们的非刚性算法成功应用于多个临床案例的MR脑图像,并显示了其价值。

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