Sticky vector fields, and other geometric measures on diffusion tensor images

L. Astola, L. Florack
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引用次数: 9

Abstract

This paper is about geometric measures in diffusion tensor imaging (DTI) analysis, and it is a continuation of our previous work (L. Astola et al., 2007), where we discussed two measures for diffusion tensor (DT) image (fiber tractography) analysis. Its contribution is threefold. First, we show how the so called connectivity measure performs on a real DTI image with three different interpolation methods. Secondly, we introduce a new vector field on DTI images, that points out the locally most coherent direction for fiber tracking, and we illustrate it on bundles of tracked fibers. Thirdly, we introduce an inhomogeneity- (edge-, crossing-) detector for symmetric positive matrix valued images, including DTI images. One possible application is segmentation of diffusion tensor fields.
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粘矢量场,以及扩散张量图像上的其他几何度量
本文是关于扩散张量成像(DTI)分析中的几何度量,它是我们之前工作的延续(L. Astola等人,2007),在那里我们讨论了扩散张量成像(DT)图像(纤维束图)分析的两个度量。它的贡献是三重的。首先,我们用三种不同的插值方法展示了所谓的连通性度量如何在真实的DTI图像上执行。其次,我们在DTI图像上引入了一个新的矢量场,指出了光纤跟踪的局部最相干方向,并在被跟踪的光纤束上进行了说明。第三,我们引入了对称正矩阵值图像(包括DTI图像)的非均匀性(边缘、交叉)检测器。一个可能的应用是扩散张量场的分割。
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