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一种用于丘脑勾勒的DTI可视化的新型对比剂。

A Novel Contrast for DTI Visualization for Thalamus Delineation.

作者信息

Fan Xian, Thompson Meredith, Bogovic John A, Bazin Pierre-Louis, Prince Jerry L

机构信息

Johns Hopkins University, Baltimore, MD.

Johns Hopkins University, Baltimore, MD ; North Carolina State University, Raleigh, NC.

出版信息

Proc SPIE Int Soc Opt Eng. 2010 Feb 13;7625. doi: 10.1117/12.844473.

Abstract

It has been recently shown that thalamic nuclei can be automatically segmented using diffusion tensor images (DTI) under the assumption that principal fiber orientation is similar within a given nucleus and distinct between adjacent nuclei. Validation of these methods, however, is challenging because manual delineation is hard to carry out due to the lack of images showing contrast between the nuclei. In this paper, we present a novel gray-scale contrast for DTI visualization that accentuates voxels in which the orientations of the principal eigenvectors are changing, thus providing an edge map for the delineation of some thalamic nuclei. The method uses the principal fiber orientation computed from the diffusion tensors computed at each voxel. The three-dimensional orientations of the principal eigenvectors are represented as five dimensional vectors and the spatial gradient (matrix) of these vectors provide information about spatial changes in tensor orientation. In particular, an edge map is created by computing the Frobenius norm of this gradient matrix. We show that this process reveals distinct edges between large nuclei in the thalamus, thereby making manual delineation of the thalamic nuclei possible. We briefly describe a protocol for the manual delineation of thalamic nuclei based on this edge map used in conjunction with a registered T1-weighted MR image, and present a preliminary multi-rater evaluation of the volumes of thalamic nuclei in several subjects.

摘要

最近的研究表明,在给定核团内主纤维方向相似且相邻核团之间不同的假设下,可以使用扩散张量图像(DTI)自动分割丘脑核团。然而,由于缺乏显示核团之间对比度的图像,手动勾勒这些核团具有挑战性,因此对这些方法进行验证很困难。在本文中,我们提出了一种用于DTI可视化的新型灰度对比度,它突出了主特征向量方向发生变化的体素,从而为一些丘脑核团的勾勒提供了边缘图。该方法使用从每个体素处计算的扩散张量中计算出的主纤维方向。主特征向量的三维方向表示为五维向量,这些向量的空间梯度(矩阵)提供了关于张量方向空间变化的信息。特别地,通过计算该梯度矩阵的Frobenius范数来创建边缘图。我们表明,这个过程揭示了丘脑大核团之间明显的边缘,从而使手动勾勒丘脑核团成为可能。我们简要描述了一种基于此边缘图并结合配准的T1加权MR图像手动勾勒丘脑核团的方案,并展示了对几个受试者丘脑核团体积的初步多评估者评估结果。

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