Abstract

Magnetic resonance spectroscopy (MRS) has been shown to be useful in several applications, and particularly in brain tumor diagnosis. However, MRS data have to be processed and classified to extract the desired information. This requires certain facilities that are not always available in hospitals. Therefore, efforts are nowadays focused on the development of automatic decision support systems (DSS). In this article, the main MRS quantification and pattern recognition methods are reviewed. Keywords: magnetic resonance spectroscopy; quantification; classification; brain tumor recognition; long and short echotime; semiparametric modeling

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