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Determination of neural fiber connections based on data structure algorithm.

Duru DG, Ozkan M - Comput Intell Neurosci (2009)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomedical Engineering, Bogazici University, 34684 Istanbul, Turkey. gokseld@boun.edu.tr

ABSTRACT
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.

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Tracking results of the implementation are represented on 2 consecutive slices.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig5: Tracking results of the implementation are represented on 2 consecutive slices.

Mentions: The selection of the investigated brain region's size is directly related with the elapsed time of the computation. To be able to visualize the results of the algorithm, not the whole brain volume but only a selected and easily recognized region is computed. The results of such an example are represented in Figures 5 and 6 from different view angles in 3D.


Determination of neural fiber connections based on data structure algorithm.

Duru DG, Ozkan M - Comput Intell Neurosci (2009)

Tracking results of the implementation are represented on 2 consecutive slices.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2801001&req=5

fig5: Tracking results of the implementation are represented on 2 consecutive slices.
Mentions: The selection of the investigated brain region's size is directly related with the elapsed time of the computation. To be able to visualize the results of the algorithm, not the whole brain volume but only a selected and easily recognized region is computed. The results of such an example are represented in Figures 5 and 6 from different view angles in 3D.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomedical Engineering, Bogazici University, 34684 Istanbul, Turkey. gokseld@boun.edu.tr

ABSTRACT
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.

Show MeSH