Limits...
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.

Show MeSH
Calculated principal eigenvectors of the entire slice superimposed on axial brain MR image.
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2801001&req=5

fig3: Calculated principal eigenvectors of the entire slice superimposed on axial brain MR image.

Mentions: Following the promising results of the synthetic data implementations, the method is applied on real DT brain images. As explained in detail in Section 2.1 ((3) and (4)), the eigensystem of D is determined by PCA [19] and interpreted graphically as seen in Figure 3.


Determination of neural fiber connections based on data structure algorithm.

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

Calculated principal eigenvectors of the entire slice superimposed on axial brain MR image.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig3: Calculated principal eigenvectors of the entire slice superimposed on axial brain MR image.
Mentions: Following the promising results of the synthetic data implementations, the method is applied on real DT brain images. As explained in detail in Section 2.1 ((3) and (4)), the eigensystem of D is determined by PCA [19] and interpreted graphically as seen in Figure 3.

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