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Abstract #4242

A Time Series Analysis Method to Achieve Improved Water Suppression in 1H MRS

Keshav Datta1,2 and Daniel Mark Spielman1,2

1Radiology, Stanford University, Stanford, CA, United States, 2Electrical Engineering, Stanford University, Stanford, CA, United States

Adequate suppression of water signal is vital in detecting low concentration metabolites in in-vivo proton spectroscopy acquisitions. This problem, which is exacerbated in the presence of multiplicative noise induced by physiological motion, is not addressed by current water and lipid saturation-based approaches. Here we use a time series modeling approach and show that signal estimation techniques are extremely effective in suppressing the highly correlated physiological noise component to achieve over three orders of magnitude in-vivo water suppression.

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