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通过脑图谱和弥散张量数据配准对跨被试的纤维束进行评估。

Evaluation of fiber bundles across subjects through brain mapping and registration of diffusion tensor data.

机构信息

Department of Computer Science, Wayne State University, Detroit, MI, USA.

出版信息

Neuroimage. 2011 Jan;54 Suppl 1:S165-75. doi: 10.1016/j.neuroimage.2010.05.085. Epub 2010 Jun 12.

Abstract

This paper presents a visualization and analysis framework for evaluating changes in structural organization of fiber bundles in human brain white matter. Statistical analysis of fiber bundle organization is conducted using an anisotropy measure, volume ratio (VR), which is ratio of anisotropic and isotropic components. Initially fiber bundles are tracked using a probabilistic algorithm starting from seed voxels. To ensure accurate selection of seed voxels and to prevent operator bias, a reference brain (MNI_152) is used when marking ROIs. Individual structural MRI brain scans are mapped to the reference using volumetric conformal parameterization. This mapping preserves topology and aligns features perfectly making it a robust and accurate registration technique. One-to-one mapping to the template allows ROI selection and subsequent transfer of ROI to structural MRI of subject. Affine registration coregisters structural MRI and DTI. Seed voxels are mapped to DTI using the resulting transformation parameters. To evaluate the proposed approach, MRI and DTI of 12 normal volunteers and 15 medial temporal lobe epilepsy patients are used. First, a statistical hypothesis testing is conducted to test for anisotropy changes in cingulum and fornix fiber bundles of epileptic patients. Experimental results reveal a 40% decrease in anisotropy levels of cingulum in patients compared to volunteers. They also show a 25% overall decrease in anisotropy of fornix. Secondly, shapes of the bundles are visualized in 3D illustrating that the bundles of epileptic patients are bumpy while those of normal volunteers are smooth.

摘要

本文提出了一种可视化和分析框架,用于评估人脑白质纤维束结构组织的变化。使用各向异性度量(VR),即各向异性和各向同性分量的比值,对纤维束组织进行统计分析。最初,从种子体素开始使用概率算法跟踪纤维束。为了确保种子体素的准确选择并防止操作员偏差,在标记 ROI 时使用参考大脑(MNI_152)。个体结构 MRI 脑扫描使用体积共形参数化映射到参考。这种映射保留拓扑并完美对齐特征,使其成为一种强大而准确的配准技术。到模板的一对一映射允许选择 ROI 并将 ROI 随后转移到主体的结构 MRI。仿射配准对结构 MRI 和 DTI 进行配准。使用所得的变换参数将种子体素映射到 DTI。为了评估所提出的方法,使用 12 名正常志愿者和 15 名内侧颞叶癫痫患者的 MRI 和 DTI。首先,进行统计假设检验以测试癫痫患者的扣带束和穹窿纤维束的各向异性变化。实验结果表明,与志愿者相比,患者的扣带束各向异性水平降低了 40%。它们还显示穹窿的各向异性总体降低了 25%。其次,以 3D 形式可视化束的形状,表明癫痫患者的束是凹凸不平的,而正常志愿者的束是平滑的。

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