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Proceedings Paper

Reconstruction of major fibers using 7T multi-shell Hybrid Diffusion Imaging in mice
Author(s): Madelaine Daianu; Russell E. Jacobs; Berislav V. Zlokovic; Axel Montagne; Paul M. Thompson
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Paper Abstract

Diffusion weighted imaging (DWI) can reveal the orientation of the underlying fiber populations in the brain. High angular resolution diffusion imaging (HARDI) is increasingly used to better resolve the orientation and mixing of fibers. Here, we assessed the added value of multi-shell q-space sampling on the reconstruction of major fibers using mathematical frameworks from q-ball imaging (QBI) and generalized q-sampling imaging (GQI), as compared to diffusion tensor imaging (DTI). We scanned a healthy mouse brain using 7-Tesla 5-shell HARDI (b=1000, 3000, 4000, 8000, 12000 s/mm2), also known as hybrid diffusion imaging (HYDI). We found that QBI may provide greater reconstruction accuracy for major fibers, which improves with the addition of higher b-value shells, unlike GQI or DTI (as expected). Although QBI is a special case of GQI, the major fiber orientation in QBI was more closely related to the orientation in DTI, rather than GQI. HYDI can aid the clinical outcomes of research and especially – more advanced human and animal connectomics projects to map the brain’s neural pathways and networks.

Paper Details

Date Published: 22 December 2015
PDF: 6 pages
Proc. SPIE 9681, 11th International Symposium on Medical Information Processing and Analysis, 968109 (22 December 2015); doi: 10.1117/12.2207946
Show Author Affiliations
Madelaine Daianu, Univ. of Southern California (United States)
Univ. of California, Los Angeles (United States)
Russell E. Jacobs, California Institute of Technology (United States)
Berislav V. Zlokovic, Univ. of Southern California (United States)
Axel Montagne, Univ. of Southern California (United States)
Paul M. Thompson, Univ. of Southern California (United States)
Univ. of California, Los Angeles (United States)


Published in SPIE Proceedings Vol. 9681:
11th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Juan D. García-Arteaga; Jorge Brieva, Editor(s)

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