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Fast GL(n)-Invariant Framework for Tensors Regularization

机译:用于张量正则化的快速GL(n)-不变框架

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摘要

We propose a novel framework for regularization of symmetric positive-definite (SPD) tensors (e.g., diffusion tensors). This framework is based on a local differential geometric approach. The manifold of symmetric positive-definite (SPD) matrices, P n , is parameterized via the Iwasawa coordinate system. In this framework distances on P n are measured in terms of a natural GL(n)-invariant metric. Via the mathematical concept of fiber bundles, we describe the tensor-valued image as a section where the metric over the section is induced by the metric over P n . Then, a functional over the sections accompanied by a suitable data fitting term is defined. The variation of this functional with respect to the Iwasawa coordinates leads to a set of frac12n(n+1)frac{1}{2}n(n+1) coupled equations of motion. By means of the gradient descent method, these equations of motion define a Beltrami flow over P n . It turns out that the local coordinate approach via the Iwasawa coordinate system results in very simple numerics that leads to fast convergence of the algorithm. Regularization results as well as results of fibers tractography for DTI are presented.
机译:我们为对称正定(SPD)张量(例如扩散张量)的正则化提出了一种新颖的框架。该框架基于局部微分几何方法。对称正定(SPD)矩阵的流形P n 通过Iwasawa坐标系进行参数化。在此框架中,P n 上的距离是根据自然GL(n)不变度量来衡量的。通过纤维束的数学概念,我们将张量值图像描述为一个截面,其中截面上的度量由P n 上的度量引起。然后,定义了带有适当数据拟合项的部分功能。此函数相对于Iwasawa坐标的变化导致一组frac12n(n + 1)frac {1} {2} n(n + 1)耦合运动方程。通过梯度下降法,这些运动方程式定义了P n 上的Beltrami流。事实证明,通过Iwasawa坐标系的局部坐标方法会产生非常简单的数值,从而导致算法的快速收敛。提出了DTI的正则化结果以及纤维束摄影的结果。

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