In susceptibility-weighted MRI, ignoring the magnetic field inhomogeneity can lead to severe reconstruction artifacts. Correcting for the effects of magnetic field inhomogeneity requires accurate fieldmaps. Especially in functional MRI, dynamic updates are desirable, since the fieldmap may change in time. Also, susceptibility effects that induce field inhomogeneity often have non-zero throughplane gradients, which, if uncorrected, can cause signal loss in the reconstructed images. Most image reconstruction methods that compensate for field inhomogeneity, even using dynamic fieldmap updates, ignore through-plane fieldmap gradients. This work proposes a computationally efficient, model based iterative method for joint reconstruction of image and dynamic fieldmap that accounts for the through-plane gradients of the field inhomogeneity. The proposed method allows for efficient reconstruction by applying fast approximations that allow the use of the conjugate gradient algorithm along with FFTs.
['Antonios Matakos', 'Jeffrey A. Fessler']
Dynamic MR image and fieldmap joint reconstruction accounting for through-plane fieldmap gradients