Velocity spectrum imaging using radial k-t SPIRiT
D relates the reconstructed Cartesian k-t data, x, to the measured k-t points, y. b Every Cartesian k-t sample point is expressed as linear combination of neighboring points in dynamic k-t space across all coils. c The shift-invariant interpolation kernel weights (indicated by the arrows in the gree...
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Published in | Journal of cardiovascular magnetic resonance Vol. 14; no. S1; p. W59 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
New York
BioMed Central
01.02.2012
BioMed Central Ltd Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | D relates the reconstructed Cartesian k-t data, x, to the measured k-t points, y. b Every Cartesian k-t sample point is expressed as linear combination of neighboring points in dynamic k-t space across all coils. c The shift-invariant interpolation kernel weights (indicated by the arrows in the green neighborhood-mask) in G are obtained by fitting them to the fully sampled k-t calibration area in a Tikhonov-regularized least-squares sense. d Unconstrained Lagrangian, where I denotes identity and Î a regularization parameter. D relates the reconstructed Cartesian k-t data, x, to the measured k-t points, y. b Every Cartesian k-t sample point is expressed as linear combination of neighboring points in dynamic k-t space across all coils. c The shift-invariant interpolation kernel weights (indicated by the arrows in the green neighborhood-mask) in G are obtained by fitting them to the fully sampled k-t calibration area in a Tikhonov-regularized least-squares sense. d Unconstrained Lagrangian, where I denotes identity and Î a regularization parameter. |
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ISSN: | 1532-429X 1097-6647 1532-429X |
DOI: | 10.1186/1532-429X-14-S1-W59 |