Meeting Banner
Abstract #5610

Robust Water-Fat Separation in Multi-Echo GRE Sequence using Patch-Based Neural Network

JaeJin Cho1, Kinam Kwon1, Seohee So1, Byungjai Kim1, and HyunWook Park1

1Korea Advanced Institute of Science and Technology (KAIST), DaeJeon, Republic of Korea

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.

This abstract and the presentation materials are available to members only; a login is required.

Join Here