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Retrospective correction of surface coil MR images using an automatic segmentation and modeling approach

dc.contributor.authorRoss, Brian D.en_US
dc.contributor.authorBland, Peyton H.en_US
dc.contributor.authorGarwood, Michaelen_US
dc.contributor.authorMeyer, Charles R.en_US
dc.date.accessioned2006-04-28T17:02:59Z
dc.date.available2006-04-28T17:02:59Z
dc.date.issued1997-05en_US
dc.identifier.citationRoss, Brian D.; Bland, Peyton; Garwood, Michael; Meyer, Charles R. (1997)."Retrospective correction of surface coil MR images using an automatic segmentation and modeling approach." NMR in Biomedicine 10(3): 125-128. <http://hdl.handle.net/2027.42/38535>en_US
dc.identifier.issn0952-3480en_US
dc.identifier.issn1099-1492en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/38535
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=9408921&dopt=citationen_US
dc.description.abstractThe use of surface coils in magnetic resonance imaging offers significant improvements in the signal-to-noise ratio over volume coils for many applications. However, the inhomogeneous reception profile of surface coils hampers their usefulness by introducing significant nonuniformities or intensity variations which can vary by greater than six-fold across the sample. In this study, we evaluated an automatic technique for retrospective correction of intensity variations observed in a high-resolution surface coil MR image of the rat brain obtained using an adiabatic magnetic resonance imaging sequence. The images are shown to have a coefficient of variation less than 12% following application of this correction algorithm. This image intensity correction technique can be applied retrospectively to all data sets and corrects both sample/patient dependent effects (e.g. attenuation of overlying tissue) or sample independent effects (e.g. coil geometry or position). This approach should also prove valuable in improving regions of interest analysis, volume histograms and thresholding techniques. © 1997 John Wiley & Sons, Ltd.en_US
dc.format.extent96 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/octet-stream
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherJohn Wiley & Sons, Ltd.en_US
dc.subject.otherChemistryen_US
dc.subject.otherAnalytical Chemistry and Spectroscopyen_US
dc.titleRetrospective correction of surface coil MR images using an automatic segmentation and modeling approachen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelElectrical Engineeringen_US
dc.subject.hlbsecondlevelPhysicsen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Radiology, School of Medicine, University of Michigan Medical Center, Ann Arbor, MI 48109–0648, USA ; Department of Radiology, School of Medicine, University of Michigan Medical Center, Ann Arbor, MI 48109–0648, USAen_US
dc.contributor.affiliationumDepartment of Radiology, School of Medicine, University of Michigan Medical Center, Ann Arbor, MI 48109–0648, USAen_US
dc.contributor.affiliationumDepartment of Radiology, School of Medicine, University of Michigan Medical Center, Ann Arbor, MI 48109–0648, USAen_US
dc.contributor.affiliationotherDepartment of Radiology, University of Minnesota, Center for Magnetic Resonance Research, Minneapolis, MN 55455, USAen_US
dc.identifier.pmid9408921en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/38535/1/sgml.10068en_US
dc.identifier.doihttp://dx.doi.org/10.1002/(SICI)1099-1492(199705)10:3<125::AID-NBM456>3.0.CO;2-Nen_US
dc.identifier.sourceNMR in Biomedicineen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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