Two-tensor streamline tractography through white matter intra-voxel fiber crossings: Assessedby fMRI

TY - GEN

T1 - Two-tensor streamline tractography through white matter intra-voxel fiber crossings

T2 - IEEE Computer society Conference on Computer Vision and Pattern Recognition Workshops

AU - Qazi, Arish Asif

AU - Kindlmann, G

AU - O'Donnell, L

AU - Peled, S

AU - Radmanesh, A

AU - Whalen, S

AU - Golby, A.J.

AU - Westin, C-F

PY - 2008

Y1 - 2008

N2 - An inherent drawback of the traditional diffusion tensor model is its limited ability to provide detailed information about multidirectional fiber architecture within a voxel. This leads to erroneous fiber tractography results in locations where fiber bundles cross each other. In this paper, we present a deterministic two-tensor extended Streamline Tractography (XST) technique, which successfully traces through regions of crossing fibers. The method has been evaluated on simulated and in-vivo human brain data, and compared with the traditional single tensor, and a probabilistic tractography technique. By tracing the corticospinal tract we demonstrate that when compared to the two methods, our technique can accurately identify fiber bundles known to be consistent with anatomy. When compared to the dense connectivity maps generated by probabilistic tractography, the method is computationally efficient and generates discrete geometric pathways that are simple to visualize and clinically useful.

AB - An inherent drawback of the traditional diffusion tensor model is its limited ability to provide detailed information about multidirectional fiber architecture within a voxel. This leads to erroneous fiber tractography results in locations where fiber bundles cross each other. In this paper, we present a deterministic two-tensor extended Streamline Tractography (XST) technique, which successfully traces through regions of crossing fibers. The method has been evaluated on simulated and in-vivo human brain data, and compared with the traditional single tensor, and a probabilistic tractography technique. By tracing the corticospinal tract we demonstrate that when compared to the two methods, our technique can accurately identify fiber bundles known to be consistent with anatomy. When compared to the dense connectivity maps generated by probabilistic tractography, the method is computationally efficient and generates discrete geometric pathways that are simple to visualize and clinically useful.

U2 - 10.1109/CVPRW.2008.4563001

DO - 10.1109/CVPRW.2008.4563001

M3 - Article in proceedings

SN - 978-1-4244-2339-2

VL - 1-3

SP - 1

EP - 8

BT - CVPR Workshops 2008

PB - IEEE Communications Society

Y2 - 23 June 2008 through 28 June 2008

ER -