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Title
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Super-resolution reconstruction of diffusion parameters from diffusion-weighted images with different slice orientations
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Author
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Abstract
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| Purpose Diffusion MRI is hampered by long acquisition times, low spatial resolution, and a low signal-to-noise ratio. Recently, methods have been proposed to improve the trade-off between spatial resolution, signal-to-noise ratio, and acquisition time of diffusion-weighted images via super-resolution reconstruction (SRR) techniques. However, during the reconstruction, these SRR methods neglect the q-space relation between the different diffusion-weighted images. Method An SRR method that includes a diffusion model and directly reconstructs high resolution diffusion parameters from a set of low resolution diffusion-weighted images was proposed. Our method allows an arbitrary combination of diffusion gradient directions and slice orientations for the low resolution diffusion-weighted images, optimally samples the q- and k-space, and performs motion correction with b-matrix rotation. Results Experiments with synthetic data and in vivo human brain data show an increase of spatial resolution of the diffusion parameters, while preserving a high signal-to-noise ratio and low scan time. Moreover, the proposed SRR method outperforms the previous methods in terms of the root-mean-square error. Conclusion The proposed SRR method substantially increases the spatial resolution of MRI that can be obtained in a clinically feasible scan time. |
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Language
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English
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Source (journal)
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Magnetic resonance in medicine. - Orlando, Fla
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Publication
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Orlando, Fla
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2016
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ISSN
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0740-3194
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DOI
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10.1002/MRM.25597
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Volume/pages
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75
:1
(2016)
, p. 181-195
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ISI
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000367739200018
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Pubmed ID
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25613283
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Full text (Publisher's DOI)
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Full text (open access)
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Full text (publisher's version - intranet only)
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