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Many approaches have been considered for automatic grading of brain tumours by means of pattern recognition with magnetic resonance spectroscopy (MRS). Providing an improved technique which can assist clinicians in accurately identifying brain tumour grades is our main objective. The proposed technique, which is based on the discrete wavelet transform (DWT) of whole-spectral or subspectral information of key metabolites, combined with unsupervised learning, inspects the separability of thedoi:10.1109/tbme.2015.2448232 pmid:26111385 fatcat:insztmlwnvf5nb6o7tyyodpdly