title: High-pass GRAPPA: an image support reduction technique for improved partially parallel imaging.
abstract: Partially parallel imaging (PPI) is a widely used technique in clinical applications. A limitation of this technique is the strong noise and artifact in the reconstructed images when high reduction factors are used. This work aims to increase the clinical applicability of PPI by improving its performance at high reduction factors. A new concept, image support reduction, is introduced. A systematic filter-design approach for image support reduction is proposed. This approach shows more advantages when used with an important existing PPI technique, GRAPPA. An improved GRAPPA method, high-pass GRAPPA (hp-GRAPPA), was developed based on this approach. The new technique does not involve changing the original GRAPPA kernel and performs reconstruction in almost the same amount of time. Experimentally, it is demonstrated that the reconstructed images using hp-GRAPPA have much lower noise/artifact level than those reconstructed using GRAPPA.
authors.affiliation: Advanced Concept Development, Invivo Corp., 3545 SW 47th Ave., Gainesville, FL 32608, USA. fhuang@invivocorp.com
authors.forename: Feng
authors.initials: F
authors.lastname: Huang
authors.forename: Yu
authors.initials: Y
authors.lastname: Li
authors.forename: Sathya
authors.initials: S
authors.lastname: Vijayakumar
authors.forename: Sarah
authors.initials: S
authors.lastname: Hertel
authors.forename: George R
authors.initials: GR
authors.lastname: Duensing
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001931:Brain Mapping / Q000379:methods*; D006321:Heart / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*