Publikationstyp: Beitrag in wissenschaftlicher Zeitschrift
Art der Begutachtung: Peer review (Publikation)
Titel: Resolving fiber crossing using advanced fast marching tractography based on diffusion tensor imaging
Autor/-in: Staempfli, Philipp
Järmann, Thomas
Crelier, G.R.
Kollias, S.
Valavanis, A.
Boesiger, Peter
DOI: 10.1016/j.neuroimage.2005.09.027
Erschienen in: NeuroImage
Band(Heft): 30
Heft: 1
Seite(n): 110
Seiten bis: 120
Erscheinungsdatum: Mär-2006
Verlag / Hrsg. Institution: Elsevier
ISSN: 1053-8119
1095-9572
Sprache: Englisch
Schlagwörter: Algorithms; Axons; Brain; Brain mapping; Computer simulation; Diffusion Magnetic Resonance Imaging; Humans; Image enhancement; Computer-assisted image processing; Three-Dimensional imaging; Mathematical computing; Neurological models; Nerve fibers; Neural pathways
Fachgebiet (DDC): 616.8: Neurologie und Krankheiten des Nervensystems
Zusammenfassung: Magnetic resonance diffusion tensor tractography is a powerful tool for the non-invasive depiction of the white matter architecture in the human brain. However, due to limitations in the underlying tensor model, the technique is often unable to reconstruct correct trajectories in heterogeneous fiber arrangements, such as axonal crossings. A novel tractography method based on fast marching (FM) is proposed which is capable of resolving fiber crossings and also permits trajectories to branch. It detects heterogeneous fiber arrangements by incorporating information from the entire diffusion tensor. The FM speed function is adapted to the local tensor characteristics, allowing in particular to maintain the front evolution direction in crossing situations. In addition, the FM's discretization error is reduced by increasing the number of considered possible front evolution directions. The performance of the technique is demonstrated in artificial data and in the healthy human brain. Comparisons with standard FM tractography and conventional line propagation algorithms show that, in the presence of interfering structures, the proposed method is more accurate in reconstructing trajectories. The in vivo results illustrate that the elucidated major white matter pathways are consistent with known anatomy and that multiple crossings and tract branching are handled correctly.
URI: https://digitalcollection.zhaw.ch/handle/11475/5024
Volltext Version: Publizierte Version
Lizenz (gemäss Verlagsvertrag): Lizenz gemäss Verlagsvertrag
Departement: School of Engineering
Enthalten in den Sammlungen:Publikationen School of Engineering

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Staempfli, P., Järmann, T., Crelier, G. R., Kollias, S., Valavanis, A., & Boesiger, P. (2006). Resolving fiber crossing using advanced fast marching tractography based on diffusion tensor imaging. NeuroImage, 30(1), 110–120. https://doi.org/10.1016/j.neuroimage.2005.09.027
Staempfli, P. et al. (2006) ‘Resolving fiber crossing using advanced fast marching tractography based on diffusion tensor imaging’, NeuroImage, 30(1), pp. 110–120. Available at: https://doi.org/10.1016/j.neuroimage.2005.09.027.
P. Staempfli, T. Järmann, G. R. Crelier, S. Kollias, A. Valavanis, and P. Boesiger, “Resolving fiber crossing using advanced fast marching tractography based on diffusion tensor imaging,” NeuroImage, vol. 30, no. 1, pp. 110–120, Mar. 2006, doi: 10.1016/j.neuroimage.2005.09.027.
STAEMPFLI, Philipp, Thomas JÄRMANN, G.R. CRELIER, S. KOLLIAS, A. VALAVANIS und Peter BOESIGER, 2006. Resolving fiber crossing using advanced fast marching tractography based on diffusion tensor imaging. NeuroImage. März 2006. Bd. 30, Nr. 1, S. 110–120. DOI 10.1016/j.neuroimage.2005.09.027
Staempfli, Philipp, Thomas Järmann, G.R. Crelier, S. Kollias, A. Valavanis, and Peter Boesiger. 2006. “Resolving Fiber Crossing Using Advanced Fast Marching Tractography Based on Diffusion Tensor Imaging.” NeuroImage 30 (1): 110–20. https://doi.org/10.1016/j.neuroimage.2005.09.027.
Staempfli, Philipp, et al. “Resolving Fiber Crossing Using Advanced Fast Marching Tractography Based on Diffusion Tensor Imaging.” NeuroImage, vol. 30, no. 1, Mar. 2006, pp. 110–20, https://doi.org/10.1016/j.neuroimage.2005.09.027.


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