Abstract #3845

Residual water signal removal in MR spectroscopic imaging with L2 regularization

Liangjie Lin^1,2, Michal Považan¹, Adam Berrington¹, Zhong Chen², and Peter B. Barker^1,3

¹Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ²Department of Electronic Science, Xiamen University, Xiamen, China, ³F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States

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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