Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2186
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dc.contributor.authorMumuni, A.-
dc.contributor.authorMcLean, J.-
dc.contributor.authorKrishnadas, R.-
dc.contributor.authorLopaz, R.-
dc.contributor.authorWaiter, G.-
dc.contributor.authorCavanagh, J.-
dc.contributor.authorCondon, B.-
dc.date.accessioned2018-11-20T08:44:14Z-
dc.date.available2018-11-20T08:44:14Z-
dc.date.issued2017-
dc.identifier.urihttp://hdl.handle.net/123456789/2186-
dc.description.abstractThe use of a relatively large and straight-edged voxel to acquire spectra from rather small and curved brain structures leads to data contamination in magnetic resonance spectroscopy (MRS), known as partial volume effect (PVE). PVE arises due to the inclusion of cerebrospinal fluid (CSF) in the voxel, leading to underestimation of metabolite concentrations in quantitative MRS. Among the PVE correction techniques available, voxel segmentation to remove the CSF fraction appears to be the most reproducible and reliable method. However, there has not been a comprehensive documented procedure of this technique to guide its implementation, particularly among scientists who may be interested in brain research using quantitative MRS, but lack the skill in the implementation of PVE correction, which is one of the most important corrections of the MR spectra in quantitative MRS. This paper details the procedure for PVE correction, using an example in vivo acquired spectra. A method to deal with tilted voxel placements is also suggested. Thus, this paper may serve as a step-by-step guide to the implementation of PVE correction in single-voxelen_US
dc.language.isoenen_US
dc.publisherEC PROTEOMICS AND BIOINFORMATICSen_US
dc.relation.ispartofseriesVol. 1;Issue 1.-
dc.subjectMRSen_US
dc.subjectFSLen_US
dc.subjectPartial Volume Effecten_US
dc.subjectFASTen_US
dc.subjectSingle-Voxelen_US
dc.subjectBrainen_US
dc.titleVOXEL SEGMENTATION-BASED PARTIAL VOLUME CORRECTION USING FSL: THEORY AND IMPLEMENTATIONen_US
dc.typeArticleen_US
Appears in Collections:School of Allied Health Sciences



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