Field inhomogeneities or susceptibility variations produce blurring in images acquired using non-2DFT k-space readout trajectories. This problem is more pronounced for sequences with long readout times such as spiral imaging. Theoretical and practical correction methods based on an acquired field map have been reported in the past. This paper introduces a new correction method based on the existing concept of frequency segmented correction but which is faster and theoretically more accurate. It consists of reconstructing the data at several frequencies to form a set of base images that are then added together with spatially varying linear coefficients derived from the field map. The new algorithm is applied to phantom and in vivo images acquired with projection reconstruction and spiral sequences, yielding sharply focused images.

Non-2DFT k-space readout strategies are useful in fast imaging but prone to blurring when reconstructed off resonance. Field inhomogeneities or susceptibility variations, coupled with a long readout time, are the major sources of this artifact. Correction methods based on a priori off-resonance information such as an acquired field map have been proposed in the literature. An alternative approach estimates the spatially varying off-resonance frequency from the data itself before applying a correction. In this latter approach there is a trade-off between the extent of correction and the chance of increased artifact due to estimation error. This paper introduces an improved algorithm for field map estimation which is both faster and more robust than the existing method. It uses a multi-stage estimation of the field map, starting from a coarse estimate both in frequency and space and proceeds towards higher resolution. The new algorithm is applied to phantom and in vivo images acquired with radial and spiral sequences to give sharper images.

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