Residual water signals in MRSI data may hinder the quantification of metabolite signals and thus affect the quality of final metabolite maps. A L2 regularization based post-processing method is proposed here for efficient removal of residual water signals especially in MRSI data. Using a water-basis matrix, the proposed method aims to find spectra that match the original metabolite signals, but at the same time imposes a constraint of reduced water signals. Results show that the L2 regularization based method can be a highly effective way for removing residual water signals from MRSI data of human brain.
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