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Large deformation diffeomorphic metric mapping of vector fields

机译:向量场的大变形微分度量映射

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This paper proposes a method to match diffusion tensor magnetic resonance images (DT-MRIs) through the large deformation diffeomorphic metric mapping of vector fields, focusing on the fiber orientations, considered as unit vector fields on the image volume. We study a suitable action of diffeomorphisms on such vector fields, and provide an extension of the Large Deformation Diffeomorphic Metric Mapping framework to this type of dataset, resulting in optimizing for geodesics on the space of diffeomorphisms connecting two images. Existence of the minimizers under smoothness assumptions on the compared vector fields is proved, and coarse to fine hierarchical strategies are detailed, to reduce both ambiguities and computation load. This is illustrated by numerical experiments on DT-MRI heart images.
机译:本文提出了一种通过矢量场的大变形微分度量映射来匹配扩散张量磁共振图像(DT-MRI)的方法,重点是将纤维方向视为图像体积上的单位矢量场。我们研究了亚纯像在此类矢量场上的合适作用,并为这种类型的数据集提供了大变形亚纯度量度量映射框架的扩展,从而优化了连接两个图像的亚纯空间的测地学。证明了在比较矢量场的平滑度假设下最小化器的存在,并详细描述了从粗糙到精细的分层策略,以减少模糊性和计算量。通过DT-MRI心脏图像的数值实验可以说明这一点。

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