title: Weighted H(infinity) optimization approach to parallel MR image reconstruction.
abstract: Parallel Magnetic Resonance Imaging (pMRI) is one of the most important technical advances in current MRI technology. Although many reconstruction methods have been proposed for pMRI, the reconstructed images still suffer visible artifacts especially when high acceleration is used. To improve the reconstruction quality of pMRI, this paper proposes a new reconstruction method. Instead of achieving perfect reconstruction under ideal assumptions, the proposed method uses weighted H(infinity) optimization to minimize the total reconstruction error, including that raised by the noise and uncertainty in sensitivity map. The experimental studies on in vivo data sets demonstrate that the proposed method outperforms significantly the existing methods at high acceleration.
authors.affiliation: Dept. of Elec. and Computer Sys. Engineering, Monash University, Clayton, VIC, Australia.
authors.forename: Zhaolin
authors.initials: Z
authors.lastname: Chen
authors.forename: Jingxin
authors.initials: J
authors.lastname: Zhang
authors.forename: Li
authors.initials: L
authors.lastname: Chai
mesh_terms: D000054:Acceleration; D000465:Algorithms; D016477:Artifacts; D049628:Body Size; D001835:Body Weight; D003627:Data Interpretation, Statistical; D004867:Equipment Design; D006257:Head / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000295:instrumentation* / Q000379:methods; D015233:Models, Statistical; D009068:Movement; D009206:Myocardium / Q000473:pathology; D012984:Software