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Robust myelin water quantification: averaging vs. spatial filtering.

Craig K Jones·Kenneth P Whittall·Alex L MacKay
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Abstract

The myelin water fraction is calculated, voxel-by-voxel, by fitting decay curves from a multi-echo data acquisition. Curve-fitting algorithms require a high signal-to-noise ratio to separate T(2) components in the T(2) distribution. This work compared the effect of averaging, during acquisition, to data postprocessed with a noise reduction filter. Forty regions, from five volunteers, were analyzed. A consistent decrease in the myelin water fraction variability with no bias in the mean was found for all 40 regions. Images of the myelin water fraction of white matter were more contiguous and had fewer "holes" than images of myelin water fractions from unfiltered echoes. Spatial filtering was effective for decreasing the variability in myelin water fraction calculated from 4-average multi-echo data.

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AlgorithmsAnisotropyBrainBrain ChemistryCorpus CallosumDiffusion Magnetic Resonance ImagingHumansImage EnhancementMyelin SheathSignal Processing, Computer-AssistedWaterComparative StudyEvaluation StudyJournal ArticleValidation Study

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Craig K Jones, Kenneth P Whittall, Alex L MacKay. 2003. Robust myelin water quantification: averaging vs. spatial filtering.. https://doi.org/10.1002/mrm.10492

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