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Determination of Neural Fiber Connections Based on Data Structure Algorithm

机译:基于数据结构算法的神经纤维连接确定

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The brain activity during perception or cognition is mostly examined by functional magnetic resonance imaging (fMRI). However, the cause of the detected activity relies on the anatomy. Diffusion tensor magnetic resonance imaging (DTMRI) as a noninvasive modality providing in vivo anatomical information allows determining neural fiber connections which leads to brain mapping. Still a complete map of fiber paths representing the human brain is missing in literature. One of the main drawbacks of reliable fiber mapping is the correct detection of the orientation of multiple fibers within a single imaging voxel. In this study a method based on linear data structures is proposed to define the fiber paths regarding their diffusivity. Another advantage of the proposed method is that the analysis is applied on entire brain diffusion tensor data. The implementation results are promising, so that the method will be developed as a rapid fiber tractography algorithm for the clinical use as future study.
机译:感知或认知过程中的大脑活动主要通过功能磁共振成像(fMRI)进行检查。但是,检测到的活动的原因取决于解剖结构。扩散张量磁共振成像(DTMRI)作为提供体内解剖学信息的非侵入性方式,可以确定导致大脑作图的神经纤维连接。仍然缺少代表人类大脑的纤维路径的完整图谱。可靠的光纤映射的主要缺点之一是在单个成像体素内正确检测多根光纤的方向。在这项研究中,提出了一种基于线性数据结构的方法来定义有关其扩散率的光纤路径。所提出的方法的另一个优点是将分析应用于整个脑扩散张量数据。实施结果是有希望的,因此该方法将被开发为一种快速纤维束照相术算法,以供将来临床研究使用。

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