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一种基于使用连续跟踪算法和双张量模型进行纤维分配的改进型纤维跟踪算法。

An improved fiber tracking algorithm based on fiber assignment using the continuous tracking algorithm and two-tensor model.

作者信息

Zhu Liuhong, Guo Gang

机构信息

Department of Radiology, Xiamen Second Hospital, Teaching Hospital of Fujian Medical University, Xiamen 361021, Fujian Province, China.

出版信息

Neural Regen Res. 2012 Jul 25;7(21):1667-74. doi: 10.3969/j.issn.1673-5374.2012.21.010.

Abstract

This study tested an improved fiber tracking algorithm, which was based on fiber assignment using a continuous tracking algorithm and a two-tensor model. Different models and tracking decisions were used by judging the type of estimation of each voxel. This method should solve the cross-track problem. This study included eight healthy subjects, two axonal injury patients and seven demyelinating disease patients. This new algorithm clearly exhibited a difference in nerve fiber direction between axonal injury and demyelinating disease patients and healthy control subjects. Compared with fiber assignment with a continuous tracking algorithm, our novel method can track more and longer nerve fibers, and also can solve the fiber crossing problem.

摘要

本研究测试了一种改进的纤维追踪算法,该算法基于使用连续追踪算法和双张量模型的纤维分配。通过判断每个体素的估计类型来使用不同的模型和追踪决策。该方法应能解决交叉追踪问题。本研究纳入了8名健康受试者、2名轴突损伤患者和7名脱髓鞘疾病患者。这种新算法清楚地显示出轴突损伤患者、脱髓鞘疾病患者与健康对照受试者之间神经纤维方向存在差异。与使用连续追踪算法进行纤维分配相比,我们的新方法能够追踪到更多更长的神经纤维,并且还能解决纤维交叉问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a7c/4308771/d3de1c8e4567/NRR-7-1667-g001.jpg

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