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December 2023

Field Map Reconstruction in Magnetic Resonance Imaging Using Bayesian Estimation

 

Fabio Baselice,Giampaolo Ferraioli andAymen Shabou
1Dipartimento per le Tecnologie, Università degli Studi di Napoli Parthenope, Naples, Italy
2Institut TELECOM, TELECOM ParisTech, CNRS LTCI, Paris, France
*Author to whom correspondence should be addressed.

Abstract

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.
Keywords: Magnetic Resonance Imagingfield map estimationphase unwrappingbayesian estimationgraph-cutsMarkov Random Field
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