Joint water–fat separation and deblurring for spiral imaging

Purpose: Most previous approaches to spiral Dixon water–fat imaging perform the water–fat separation and deblurring sequentially based on the assumption that the phase accumulation and blurring as a result of off-resonance are separable. This condition can easily be violated in regions where the B₀ inhomogeneity varies rapidly. The goal of this work is to present a novel joint water–fat separation and deblurring method for spiral imaging. Methods: The proposed approach is based on a more accurate signal model that takes into account the phase accumulation and blurring simultaneously. A conjugate gradient method is used in the image domain to reconstruct the deblurred water and fat iteratively. Spatially varying convolutions with a local convergence criterion are used to reduce the computational demand. Results: Both simulation and high-resolution brain imaging have demonstrated that the proposed joint method consistently improves the quality of reconstructed water and fat images compared with the sequential approach, especially in regions where the field inhomogeneity changes rapidly in space. The loss of signal-to-noise-ratio as a result of deblurring is minor at optimal echo times. Conclusions: High-quality water–fat spiral imaging can be achieved with the proposed joint approach, provided that an accurate field map of B₀ inhomogeneity is available. Magn Reson Med 79:3218–3228, 2018.