Field Map Reconstruction in Magnetic Resonance Imaging Using Bayesian Estimation

被引:22
作者
Baselice, Fabio [1 ]
Ferraioli, Giampaolo [1 ]
Shabou, Aymen [2 ]
机构
[1] Univ Napoli Parthenope, Dipartimento Tecnol, Naples, Italy
[2] LTCI, CNRS, TELECOM ParisTech, Inst TELECOM, Paris, France
关键词
Magnetic Resonance Imaging; field map estimation; phase unwrapping; bayesian estimation; graph-cuts; Markov Random Field; MAXIMUM-LIKELIHOOD-ESTIMATION; RICIAN DISTRIBUTION;
D O I
10.3390/s100100266
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Field inhomogeneities in Magnetic Resonance Imaging (MRI) can cause blur or image distortion as they produce off-resonance frequency at each voxel. These effects can be corrected if an accurate field map is available. Field maps can be estimated starting from the phase of multiple complex MRI data sets. In this paper we present a technique based on statistical estimation in order to reconstruct a field map exploiting two or more scans. The proposed approach implements a Bayesian estimator in conjunction with the Graph Cuts optimization method. The effectiveness of the method has been proven on simulated and real data.
引用
收藏
页码:266 / 279
页数:14
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