Chinese Journal of Tissue Engineering Research ›› 2010, Vol. 14 ›› Issue (43): 7983-7986.doi: 10.3969/j.issn.1673-8225.2010.43.002

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Nerve fiber tracking methods using diffusion tensor imaging

Ma Kai1, Wang Xiao-zhou2, Gao Dian-shuai2   

  1. 1 Computer Staff, Xuzhou Medical College, Xuzhou  221002, Jiangsu Province, China; 2 Research Centre of Neurobiology, Xuzhou Medical College, Xuzhou  221002, Jiangsu Province, China
  • Online:2010-10-22 Published:2010-10-22
  • Contact: Gao Dian-shuai, Doctor, Professor, Research Centre of Neurobiology, Xuzhou Medical College, Xuzhou 221002, Jiangsu Province, China dshgao@vip.sina.com
  • About author:Ma Kai☆, Doctor, Associate professor, Computer Staff, Xuzhou Medical College, Xuzhou 221002, Jiangsu Province, China cumtbmakai@126.com
  • Supported by:

    the Natural Science Foundation of Colleges and Universities in Jiangsu Province, No. 07KJB310117*

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Abstract:

BACKGROUND:  There are many nerve fiber tracking methods using diffusion tensor imaging (DTI) at present. It is strict and singular of data format for different methods, and these methods can track fibers in special condition. There is no uniform standard for nerve fiber tracking. Therefore, a new brief universal method is researched for the nerve fiber tracking using DTI.
OBJECTIVE: To propose a new brief universal DTI method for the nerve fiber tracking to translate into fixed data sampling format.
METHODS: Firstly, the file composed of diffusion gradient factor b was searched in DTI original image and the DICOM file was translated into Analyze data format by the software MRIcro. The Analyze data format was standardized by SPM. Finally, the fiber tracking was disposed.
RESULTS AND CONCLUSION: The method can acquire diffusion gradient factor b file accurately and effectively. We provided a new method for the nerve fiber tracking, which can translate the different original data into the fixed data format. Moreover, by this method, the nerve fiber tracking can be accurately acquired. And it provides a brief effective method for DTI research.

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