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Abstract #2855

Optimized truncation to integrate multi-channel MRS data using rank-R singular value decomposition (OpTIMUS)

Dongsuk Sung1, Benjamin B Risk2, Maame Owusu-Ansah3, Xiaodong Zhong4, Hui Mao3, and Candace Fleischer1,3
1Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States, 2Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States, 3Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States, 4MR R&D Collaborations, Siemens Healthcare, Los Angeles, CA, United States

Multi-channel phased array coils facilitate acquisition of fast, localized, and high signal-to-noise ratio (SNR) magnetic resonance spectroscopy (MRS) data. As individual spectra are acquired from multiple coil channels, it is necessary to combine these data to form a final spectrum. Here, we present an improved approach for combining multi-channel phased array data using spectral windowing followed by a rank-R singular value decomposition (SVD). Our approach, termed ‘OpTIMUS’ was evaluated using SNR and compared to combination methods including whitened SVD (WSVD), S/N2 weighting, and the vendor-supplied reconstruction. OpTIMUS generated the highest SNR across all methods.

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