The water-fat separation techniques using a multi-echo GRE sequence has suffered from an inaccurate and swapped water-fat separation results caused by several issues. In the abstract, we propose a robust water-fat separation method using patch-based neural network to overcome this problem. The neural network is trained using the relationship between the multi-echo images obtained from the multi-echo GRE sequence and the reliable water-fat separated images that are reconstructed by IDEAL from the multiple single-echo GRE acquisitions with different echo times. The in-vivo experiment results show the proposed method can successfully separate accurate water-fat images from the multi-echo GRE images in comparison with IDEAL.
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