title: Improved data reconstruction method for GRAPPA.
abstract: This paper presents an improved data reconstruction method for generalized autocalibrating partially parallel acquisitions (GRAPPA) using multicolumn multiline interpolation (MCMLI). Both nearest acquired line (ky) neighboring points and column (kx) neighboring points from all components of an array coil were used to reconstruct each missing datum through interpolation. A new fitting scheme was designed to estimate the interpolation weights. Both simulations and in vivo experiments demonstrated that the proposed method yields higher-quality data reconstruction than the original GRAPPA method, especially with high acceleration factors.
authors.affiliation: Center for Functional Neuroimaging, School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
authors.forename: Ze
authors.initials: Z
authors.lastname: Wang
authors.forename: Jiongjiong
authors.initials: J
authors.lastname: Wang
authors.forename: John A
authors.initials: JA
authors.lastname: Detre
mesh_terms: D001931:Brain Mapping; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*