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Anchorage, AK, USA
June 23, 2008 to June 28, 2008
ISBN: 978-1-4244-2339-2
pp: 1-8
Arish A. Qazi , Harvard Medical School, Boston MA, USA
Gordon Kindlmann , Harvard Medical School, Boston MA, USA
Lauren O'Donnell , Harvard Medical School, Boston MA, USA
Sharon Peled , Harvard Medical School, Boston MA, USA
Alireza Radmanesh , Harvard Medical School, Boston MA, USA
Stephen Whalen , Harvard Medical School, Boston MA, USA
Alexandra J. Golby , Harvard Medical School, Boston MA, USA
Carl-Fredrik Westin , Harvard Medical School, Boston MA, USA
ABSTRACT
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.
CITATION
Arish A. Qazi, Gordon Kindlmann, Lauren O'Donnell, Sharon Peled, Alireza Radmanesh, Stephen Whalen, Alexandra J. Golby, Carl-Fredrik Westin, "Two-tensor streamline tractography through white matter intra-voxel fiber crossings: Assessed by fMRI", CVPRW, 2008, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops 2008, pp. 1-8, doi:10.1109/CVPRW.2008.4563001
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