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White Matter Fiber Tracts Based On Diffusion Tensor Imaging

机译:基于扩散张量成像的白质纤维丝

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The recently developed magnetic resonance imaging technique of diffusion tensor imaging (DTI) has a widespread application on investigating the cerebral white matter architecture. When referred to fiber tracking, as the typical application of DTI, one of the most intuitive ways to reconstruct fiber trajectory is streamline tracking, (STT). Regarding the problems from noise and discrete tensor field in traditional STT algorithm, we introduce the concept of adjacent and previous voxels as well as the break point during fiber tracking. To evaluate the validity of our improved algorithm, we firstly applied it on the simulated data and meanwhile obtained some available values in our approach. Then the traditional STT and improved algorithm were both applied to DTI data to reconstruct the fiber trajectory. The results showed our improved method did follow the actual fiber more precisely. Future improvements were also discussed in the end of the paper.
机译:最近开发的扩散张量成像(DTI)的磁共振成像技术具有广泛应用于研究大脑白质架构。当参考光纤跟踪时,作为DTI的典型应用,重建光纤轨迹的最直观方式之一是简化跟踪,(STT)。关于传统STT算法中噪声和离散张力场的问题,我们在光纤跟踪期间介绍相邻和以前体素的概念以及断点。为了评估我们改进的算法的有效性,我们首先将其应用于模拟数据,同时在我们的方法中获得了一些可用值。然后,传统的STT和改进的算法都应用于DTI数据以重建光纤轨迹。结果表明,我们改进的方法确实更准确地遵循实际纤维。本文结束时还讨论了未来的改进。

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