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Removal of Nuisance Signals from Limited and Sparse (1)H MRSI Data Using a Union-of-Subspaces Model

PURPOSE: To remove nuisance signals (e.g., water and lipid signals) for (1)H MRSI data collected from the brain with limited and/or sparse (k, t)-space coverage. METHODS: A union-of-subspace model is proposed for removing nuisance signals. The model exploits the partial separability of both the nuis...

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Bibliografische gegevens
Gepubliceerd in:Magn Reson Med
Hoofdauteurs: Ma, Chao, Lam, Fan, Johnson, Curtis L., Liang, Zhi-Pei
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: 2015
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Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC4567537/
https://ncbi.nlm.nih.gov/pubmed/25762370
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/mrm.25635
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