Methods are described for efficient reconstruction of MRI data. In one practice, new reconstruction algorithms for non-uniformly sampled k-space data are presented. In the disclosed algorithms, Iterative Next-Neighbor re-Gridding (INNG) and Block INNG (BINNG), iterative procedures are performed using larger rescaled matrices than the target grid matrix In BINNG algorithm, the sampled k-space region is partitioned into several blocks and the INNG algorithm is applied to each block. In another practice, a novel partial spiral reconstruction (PFSR) uses an estimated phase map from a low-resolution image reconstructed from the central k-space data and performs iterations, similar to the iterative procedures with INNG, with an imposed phase constraint. According to yet another practice, an off-resonance correction is performed on matrices that are smaller than the full image matrix. All these methods reduce the computational costs while rendering high-quality reconstructed images.
CROSS-REFERENCE TO RELATED APPLICATIONS
This application incorporates by reference in entirety, and claims priority to and benefit of, the U.S. Provisional Patent Applications having the following numbers and respective filing dates: No. 60/468,177 (filed on 5 May 2003), No. 60/483,219 (filed on 27 Jun. 2003), and No. 60/485,823 (filed on 8 Jul. 2003).
