Ependymomas, medulloblastomas and pilocytic astrocytomas are common paediatric central nervous system tumours. In vivo 1H magnetic resonance spectroscopy is a non-invasive technique to determine tumour metabolic characteristics, however suffers from limited signal-to-noise ratios. Our previous studies demonstrated that metabolite concentration estimation may be improved through wavelet de-noising on both simulated and in vivo MRS data, as reflected by improved tumour classification. In this study we compared improvements in fit quality using both wavelets and apodisation on simulated and in vivo MRS data of the three tumours by measuring overall and regional SNR.
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