Abstract
A fiber tracking algorithm, called a barycentric-space weighted tractography (B WT) algorithm, was shown to improve streamline tracking technique (STT) algorithms used for creating m,ultiple connection fiber trajectories for branching and crossing. Considering the weight of diffusion anisotropy in the current and surrounding voxels, and the fact that the direction of income vector and the principal eigenvector had only a small bias towards the direction of surrounding voxels, the algorithm performed well. This was largely due to the application of m,ultiple seeds and bidirectional tracing for each fiber. Fractional isotropy (FI) related to fractional anisotropy (FA) is proposed for the purpose of determining the threshold of separate brain tissues. The white matter region was used as a mask to reduce the number of seeds in order to increase the efficiency of the fiber tracking software. Synthetic and clinical diffusion tensor imaging (DTI) data were employed to demonstrate the effectiveness of the fiber tracking algorithm. The experimental results show that the fiber visualization is reasonable.
| Original language | English |
|---|---|
| Pages (from-to) | 1339-1358 |
| Number of pages | 20 |
| Journal | International Journal of Innovative Computing, Information and Control |
| Volume | 8 |
| Issue number | 2 |
| Publication status | Published - 2012 Feb 1 |
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All Science Journal Classification (ASJC) codes
- Software
- Theoretical Computer Science
- Information Systems
- Computational Theory and Mathematics
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Weighted geometric diffusion measures for neuronal fiber tractography algorithms. / Hsu, Chih Yu; Chang, Chia Hao; Yang, Yu Jen; Tseng, Kuo Kun; Lai, Yeong Lin; Chen, Chih Cheng.
In: International Journal of Innovative Computing, Information and Control, Vol. 8, No. 2, 01.02.2012, p. 1339-1358.Research output: Contribution to journal › Article
TY - JOUR
T1 - Weighted geometric diffusion measures for neuronal fiber tractography algorithms
AU - Hsu, Chih Yu
AU - Chang, Chia Hao
AU - Yang, Yu Jen
AU - Tseng, Kuo Kun
AU - Lai, Yeong Lin
AU - Chen, Chih Cheng
PY - 2012/2/1
Y1 - 2012/2/1
N2 - A fiber tracking algorithm, called a barycentric-space weighted tractography (B WT) algorithm, was shown to improve streamline tracking technique (STT) algorithms used for creating m,ultiple connection fiber trajectories for branching and crossing. Considering the weight of diffusion anisotropy in the current and surrounding voxels, and the fact that the direction of income vector and the principal eigenvector had only a small bias towards the direction of surrounding voxels, the algorithm performed well. This was largely due to the application of m,ultiple seeds and bidirectional tracing for each fiber. Fractional isotropy (FI) related to fractional anisotropy (FA) is proposed for the purpose of determining the threshold of separate brain tissues. The white matter region was used as a mask to reduce the number of seeds in order to increase the efficiency of the fiber tracking software. Synthetic and clinical diffusion tensor imaging (DTI) data were employed to demonstrate the effectiveness of the fiber tracking algorithm. The experimental results show that the fiber visualization is reasonable.
AB - A fiber tracking algorithm, called a barycentric-space weighted tractography (B WT) algorithm, was shown to improve streamline tracking technique (STT) algorithms used for creating m,ultiple connection fiber trajectories for branching and crossing. Considering the weight of diffusion anisotropy in the current and surrounding voxels, and the fact that the direction of income vector and the principal eigenvector had only a small bias towards the direction of surrounding voxels, the algorithm performed well. This was largely due to the application of m,ultiple seeds and bidirectional tracing for each fiber. Fractional isotropy (FI) related to fractional anisotropy (FA) is proposed for the purpose of determining the threshold of separate brain tissues. The white matter region was used as a mask to reduce the number of seeds in order to increase the efficiency of the fiber tracking software. Synthetic and clinical diffusion tensor imaging (DTI) data were employed to demonstrate the effectiveness of the fiber tracking algorithm. The experimental results show that the fiber visualization is reasonable.
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M3 - Article
AN - SCOPUS:84863041496
VL - 8
SP - 1339
EP - 1358
JO - International Journal of Innovative Computing, Information and Control
JF - International Journal of Innovative Computing, Information and Control
SN - 1349-4198
IS - 2
ER -