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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Liang Zhan Leow, A.D. Siwei Zhu Ming-Chang Chiang Barysheva, M. Toga, A.W. McMahon, K.L. de Zubicaray, G.I. Wright, M.J. Thompson, P.M. |
| Copyright Year | 2009 |
| Description | Author affiliation: Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA, USA (Liang Zhan; Leow, A.D.; Ming-Chang Chiang; Barysheva, M.; Toga, A.W.; Thompson, P.M.) || University of Queensland, Functional MRI Laboratory, Centre for Magnetic Resonance, Brisbane, Australia (McMahon, K.L.; de Zubicaray, G.I.) || Queensland Institute of Medical Research, Brisbane, Australia (Wright, M.J.) || Department of Mathematics, UCLA, Los Angeles, CA, USA (Siwei Zhu) |
| Abstract | High-angular resolution diffusion imaging (HARDI) can reconstruct fiber pathways in the brain with extraordinary detail, identifying anatomical features and connections not seen with conventional MRI. HARDI overcomes several limitations of standard diffusion tensor imaging, which fails to model diffusion correctly in regions where fibers cross or mix. As HARDI can accurately resolve sharp signal peaks in angular space where fibers cross, we studied how many gradients are required in practice to compute accurate orientation density functions, to better understand the trade-off between longer scanning times and more angular precision. We computed orientation density functions analytically from tensor distribution functions (TDFs) which model the HARDI signal at each point as a unit-mass probability density on the 6D manifold of symmetric positive definite tensors. In simulated two-fiber systems with varying Rician noise, we assessed how many diffusion-sensitized gradients were sufficient to (1) accurately resolve the diffusion profile, and (2) measure the exponential isotropy (EI), a TDF-derived measure of fiber integrity that exploits the full multidirectional HARDI signal. At lower SNR, the reconstruction accuracy, measured using the Kullback-Leibler divergence, rapidly increased with additional gradients, and EI estimation accuracy plateaued at around 70 gradients. |
| Starting Page | 1402 |
| Ending Page | 1405 |
| File Size | 529680 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424439317 |
| ISSN | 19457928 |
| DOI | 10.1109/ISBI.2009.5193328 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-06-28 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image analysis Image reconstruction Image resolution Diffusion tensor imaging High-resolution imaging Tensile stress Distribution functions Signal resolution Density functional theory Noise measurement Exponential Isotropy High Angular Resolution Diffusion Imaging Tensor Distribution Function multi-fiber construction Kullback-Leibler divergence |
| Content Type | Text |
| Resource Type | Article |
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