Regularization of Diffusion Tensor Maps Using a Non-Gaussian Markov Random Field Approach

机译：使用非高斯马尔可夫随机场方法对扩散张量图进行正则化

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In this paper we propose a novel non-Gaussian MRF for reg-ularization of tensor fields for fiber tract enhancement. Two entities are considered in the model, namely, the linear component of the tensor, i.e., how much line-like the tensor is, and the angle of the eigenvector associated to the largest eigenvalue. A novel, to the best of the author's knowledge, angular density function has been proposed. Closed form expressions of the posterior densities are obtained. Some experiments are also presented for which color-coded images are visually meaningful. Finally, a quantitative measure of regularization is also calculated to validate the achieved results based on an averaged measure of entropy.

机译：在本文中，我们提出了一种新颖的非高斯MRF，用于张量场的规则化以增强纤维束。在模型中考虑了两个实体，即张量的线性分量，即张量具有多少线状，以及与最大特征值关联的特征向量的角度。据作者所知，已经提出了一种新颖的角密度函数。获得后密度的封闭形式表达。还提供了一些实验，对于这些实验，颜色编码的图像在视觉上是有意义的。最后，还基于平均熵的度量来计算正则化的量化度量，以验证所获得的结果。

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《6th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2003) Pt.II; Nov 15-18, 2003; Montreal, Canada》|2003年|p.92-100|共9页
会议地点 Montreal(CA);Montreal(CA)
作者
Marcos Martin-Fernandez; Carlos Alberola-Lopez; Juan Ruiz-Alzola; Carl-Fredrik Westin;
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E. T. S. Ingenieros de Telecomunicacion. Universidad de Valladolid 47011 Valladolid (SPAIN);

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正文语种 eng
中图分类 Q-;
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4. A Novel Gauss-Markov Random Field Approach for Regularization of Diffusion Tensor Maps [C] . Marcos Martin-Fernandez, Raul San Josa-Estepar, Carl-Fredrik Westin, 9th International Workshop on Computer Aided Systems Theory; Feb 24-28, 2003; Las Palmas de Gran Canaria, Spain . 2003

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8. Modeling and Estimation of Reciprocal Diffusion and Gauss-Markov Random Fields. [R] . 1992

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Regularization of Diffusion Tensor Maps Using a Non-Gaussian Markov Random Field Approach

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