Abstract
Data collection of MRI which is sampled nonuniformly in k-space is often interpolated onto a Cartesian grid for fast reconstruction. The collected data must be properly weighted before interpolation, for accurate reconstruction. We propose a criterion for choosing the weighting function necessary to compensate for nonuniform sampling density. A numerical iterative method to find a weighting function that meets that criterion is also given. This method uses only the coordinates of the sampled data; unlike previous methods, it does not require knowledge of the trajectories and can easily handle trajectories that 'cross' in k-space. Moreover, the method can handle sampling patterns that are undersampled in some regions of k-space and does not require a post-gridding density correction. Weighting functions for various data collection strategies are shown. Synthesized and collected in vivo data also illustrate aspects of this method.
Original language | English (US) |
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Pages (from-to) | 179-186 |
Number of pages | 8 |
Journal | Magnetic Resonance in Medicine |
Volume | 41 |
Issue number | 1 |
DOIs | |
State | Published - 1999 |
Keywords
- Gridding
- Nyquist
- Sampling density
- Spiral MRI
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging