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Regularized Field Map Estimation in MRI

dc.contributor.authorFunai, Amanda K.en_US
dc.contributor.authorFessler, Jeffrey A.en_US
dc.contributor.authorYeo, Desmond Teck Bengen_US
dc.contributor.authorOlafsson, Valur Thoren_US
dc.contributor.authorNoll, Douglas C.en_US
dc.date.accessioned2011-08-18T18:20:57Z
dc.date.available2011-08-18T18:20:57Z
dc.date.issued2008-04-22en_US
dc.identifier.citationFunai, A.K.; Fessler, J.A.; Yeo, D.; Olafsson, V.T.; Noll, D.C. (2008). "Regularized Field Map Estimation in MRI." IEEE Transactions on Medical Imaging 27(10): 1484-1494. <http://hdl.handle.net/2027.42/85871>en_US
dc.identifier.issn0278-0062en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/85871
dc.description.abstractIn fast magnetic resonance (MR) imaging with long readout times, such as echo-planar imaging (EPI) and spiral scans, it is important to correct for the effects of field inhomogeneity to reduce image distortion and blurring. Such corrections require an accurate field map, a map of the off-resonance frequency at each voxel. Standard field map estimation methods yield noisy field maps, particularly in image regions with low spin density. This paper describes regularized methods for field map estimation from two or more MR scans having different echo times. These methods exploit the fact that field maps are generally smooth functions. The methods use algorithms that decrease monotonically a regularized least-squares cost function, even though the problem is highly nonlinear. Results show that the proposed regularized methods significantly improve the quality of field map estimates relative to conventional unregularized methods.en_US
dc.publisherIEEEen_US
dc.titleRegularized Field Map Estimation in MRIen_US
dc.typearticleen_US
dc.subject.hlbsecondlevelBiomedical Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Electrical Engineering and Computer Science. Department of Biomedical Engineering.en_US
dc.identifier.pmid18815100en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/85871/1/Fessler22.pdf
dc.identifier.doi10.1109/TMI.2008.923956en_US
dc.identifier.sourceIEEE Transactions on Medical Imagingen_US
dc.owningcollnameElectrical Engineering and Computer Science, Department of (EECS)


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