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各向异性褶皱在扩散张量磁共振成像中描绘白质结构。

Anisotropy creases delineate white matter structure in diffusion tensor MRI.

作者信息

Kindlmann Gordon, Tricoche Xavier, Westin Carl-Fredrik

机构信息

Laboratory of Mathematics in Imaging, Department of Radiology, Harvard Medical School, USA.

出版信息

Med Image Comput Comput Assist Interv. 2006;9(Pt 1):126-33. doi: 10.1007/11866565_16.

Abstract

Current methods for extracting models of white matter architecture from diffusion tensor MRI are generally based on fiber tractography. For some purposes a compelling alternative may be found in analyzing the first and second derivatives of diffusion anisotropy. Anisotropy creases are ridges and valleys of locally extremal anisotropy, where the gradient of anisotropy is orthogonal to one or more eigenvectors of its Hessian. We propose that anisotropy creases provide a basis for extracting a skeleton of white matter pathways, in that ridges of anisotropy coincide with interiors of fiber tracts, and valleys of anisotropy coincide with the interfaces between adjacent but distinctly oriented tracts. We describe a crease extraction algorithm that generates high-quality polygonal models of crease surfaces, then demonstrate the method on a measured diffusion tensor dataset, and visualize the result in combination with tractography to confirm its anatomic relevance.

摘要

目前从扩散张量磁共振成像中提取白质结构模型的方法通常基于纤维束成像。出于某些目的,在分析扩散各向异性的一阶和二阶导数时可能会找到一种引人注目的替代方法。各向异性折痕是局部极值各向异性的脊和谷,其中各向异性梯度与其黑塞矩阵的一个或多个特征向量正交。我们提出,各向异性折痕为提取白质通路骨架提供了基础,因为各向异性的脊与纤维束的内部重合,而各向异性的谷与相邻但方向不同的束之间的界面重合。我们描述了一种折痕提取算法,该算法生成高质量的折痕表面多边形模型,然后在实测扩散张量数据集上演示该方法,并将结果与纤维束成像结合可视化,以确认其解剖学相关性。

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