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Nonrigid registration of brain MRI using NURBS

机译:使用NURBS进行脑MRI的非刚性配准

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摘要

The focus of medical image registration has shifted to nonrigid registration. It is also a core component in computational neuroanat-omy. In this paper, we propose an efficient registration framework which has feature of multiresolution and multigrid. In contrast to the existing registration algorithms. Free-Form Deformations based NURBS (Nonuniform Rational B Spline) are used to acquire nonrigid transformation. This can provide a competitive alternative to Free-Form Deformations based B spline on flexibility and accuracy. To our knowledge, it is the first report of the use of this mathematical tool for medical image registration. Subdivision of NURBS is extended to 3D and is used in hierarchical optimization to speed up the registration and avoid local minima. The performance of this method is numerically evaluated on simulated images and real images. Compared with the registration method using uniform Free-Form Deformations based B spline, our method can successfully register images with improved performance.
机译:医学图像配准的重点已转向非刚性配准。它也是计算神经解剖学的核心组成部分。本文提出了一种具有多分辨率,多网格的高效注册框架。与现有的注册算法相反。基于自由形变的NURBS(非均匀有理B样条)用于获取非刚性变换。这可以提供基于灵活性和准确性的基于B样条的自由形式变形的有竞争力的替代方案。据我们所知,这是该数学工具用于医学图像配准的首次报道。 NURBS的细分扩展到3D,并用于层次优化中,以加快注册速度并避免局部最小值。在模拟图像和真实图像上对这种方法的性能进行了数值评估。与使用基于B样条的统一自由形式变形的配准方法相比,我们的方法可以成功配准具有改进性能的图像。

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