## Abstract Magnetic resonance imaging with parallel data acquisition requires algorithms for reconstructing the patient's image from a small number of measured __k__‐space lines. In contrast to well‐known algorithms like SENSE and GRAPPA and its flavours we consider the problem as a non‐linear in
New strategy for reconstructing partial-Fourier imaging data in functional MRI
✍ Scribed by Xiaodong Zhang; Essa Yacoub; Xiaoping Hu
- Publisher
- John Wiley and Sons
- Year
- 2001
- Tongue
- English
- Weight
- 146 KB
- Volume
- 46
- Category
- Article
- ISSN
- 0740-3194
- DOI
- 10.1002/mrm.1296
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✦ Synopsis
Abstract
Most partial Fourier (PF) approaches use a low‐resolution phase estimate in the reconstruction to account for non‐zero phases of the image. These methods may fail when there are large phase errors, a situation commonly encountered in T‐weighted functional MRI (fMRI). To mitigate this problem, a method was developed based on the inversion of a matrix formulated according to a phase map derived from iterative reconstruction. To make this method computationally practical for fMRI, a strategy was introduced such that the matrix inversion is performed only once for each slice in the time series, assuming that the phase map remains constant in the time series. To ensure the temporal phase invariance, physiological noise correction and global phase correction were applied to the data before the reconstruction. This method was demonstrated to be robust and efficient for fMRI. Magn Reson Med 46:1045–1048, 2001. © 2001 Wiley‐Liss, Inc.
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