title: Joint estimation and correction of geometric distortions for EPI functional MRI using harmonic retrieval.
abstract: Magnetic resonance imaging (MRI) uses applied spatial variations in the magnetic field to encode spatial position. Therefore, nonuniformities in the main magnetic field can cause image distortions. In order to correct the image distortions, it is desirable to simultaneously acquire data with a field map in registration. We propose a joint estimation (JE) framework with a fast, noniterative approach using harmonic retrieval (HR) methods, combined with a multi-echo echo-planar imaging (EPI) acquisition. The connection with HR establishes an elegant framework to solve the JE problem through a sequence of 1-D HR problems in which efficient solutions are available. We also derive the condition on the smoothness of the field map in order for HR techniques to recover the image with high signal-to-noise ratio. Compared to other dynamic field mapping methods, this method is not constrained by the absolute level of the field inhomogeneity over the slice, but relies on a generous pixel-to-pixel smoothness. Moreover, this method can recover image, field map, and T2* map simultaneously.
authors.affiliation: Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. hnguyen6@illinois.edu
authors.forename: Hien M
authors.initials: HM
authors.lastname: Nguyen
authors.forename: Bradley P
authors.initials: BP
authors.lastname: Sutton
authors.forename: Robert L
authors.initials: RL
authors.lastname: Morrison
authors.forename: Minh N
authors.initials: MN
authors.lastname: Do
mesh_terms: D000162:Acoustics; D000465:Algorithms; D001931:Brain Mapping; D017352:Echo-Planar Imaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D012815:Signal Processing, Computer-Assisted