• Ying Chen, Congbo Cai, Jianhui Zhong, and Zhong Chen.
• Department of Electronics Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, State Key Laboratory for Physical Chemistry of Solid Surfaces, Xiamen University, Xiamen, China.
• Magn Reson Med. 2015 Apr 1; 73 (4): 1441-9.

PurposeTo present a new high-resolution single-point water-fat separation algorithm based on the spatiotemporally encoded chemical shift imaging technique.TheoryIdentifying water and fat peaks on the ensemble of the nominal k-space profiles of all spatiotemporally encoded lines enables evaluation of the mean off-resonance frequencies of the two components. With utilization of the spatial smoothness and filtering regularizations, the water/fat profiles can be discriminated with twice joint linear least squares estimations line-by-line.MethodsThe effectiveness of the proposed algorithm was assessed by experiments on oil-water phantoms and in vivo in rats at 7T using a spatiotemporally encoded variant of the multishot spin-echo sequence. The results were compared with those obtained from previously proposed 1-point Dixon, 2-point Dixon, and 3-point IDEAL methods.ResultsThe results demonstrate that the new technique can achieve high-quality water-fat separations, comparable in signal-to-noise ratio and contrast to the multipoint methods and is more robust in cases when large areas of low signals or motion artifacts jeopardize the results from the 1-point Dixon method.ConclusionsThe proposed technique is potentially a new viable alternative for single-point water-fat separation.© 2014 Wiley Periodicals, Inc.

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