On NUFFT-Based Gridding for Non-Cartesian MRI
dc.contributor.author | Fessler, Jeffrey A. | en_US |
dc.date.accessioned | 2011-08-18T18:20:43Z | |
dc.date.available | 2011-08-18T18:20:43Z | |
dc.date.issued | 2007-07-16 | en_US |
dc.identifier.citation | Fessler, J. A. (2007). "On NUFFT-Based Gridding for Non-Cartesian MRI." Journal of Magnetic Resonance 188(2): 191-195. <http://hdl.handle.net/2027.42/85799> | en_US |
dc.identifier.issn | 1090-7807 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/85799 | |
dc.description.abstract | For MRI with non-Cartesian sampling, the conventional approach to reconstructing images is to use the gridding method with a Kaiser–Bessel (KB) interpolation kernel. Recently, Sha et al. [L. Sha, H. Guo, A.W. Song, An improved gridding method for spiral MRI using nonuniform fast Fourier transform, J. Magn. Reson. 162(2) (2003) 250–258] proposed an alternative method based on a nonuniform FFT (NUFFT) with least-squares (LS) design of the interpolation coefficients. They described this LS_NUFFT method as shift variant and reported that it yielded smaller reconstruction approximation errors than the conventional shift-invariant KB approach. This paper analyzes the LS_NUFFT approach in detail. We show that when one accounts for a certain linear phase factor, the core of the LS_NUFFT interpolator is in fact real and shift invariant. Furthermore, we find that the KB approach yields smaller errors than the original LS_NUFFT approach. We show that optimizing certain scaling factors can lead to a somewhat improved LS_NUFFT approach, but the high computation cost seems to outweigh the modest reduction in reconstruction error. We conclude that the standard KB approach, with appropriate parameters as described in the literature, remains the practical method of choice for gridding reconstruction in MRI. | en_US |
dc.publisher | Elsevier | en_US |
dc.title | On NUFFT-Based Gridding for Non-Cartesian MRI | en_US |
dc.type | article | en_US |
dc.subject.hlbsecondlevel | Biomedical Engineering | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.identifier.pmid | 17689121 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/85799/1/Fessler32.pdf | |
dc.identifier.doi | 10.1016/j.jmr.2007.06.012 | en_US |
dc.identifier.source | Journal of Magnetic Resonance | en_US |
dc.owningcollname | Electrical Engineering and Computer Science, Department of (EECS) |
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