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Abstract #2704

Accelerated Water-Fat Imaging using Restricted Subspace Fieldmap Estimation

Samir D. Sharma1, Houchun H. Hu1, Krishna S. Nayak1

1Electrical Engineering, University of Southern California, Los Angeles, CA, United States

Water-fat separation based on multi-echo methods play an important role in several clinical applications because they reliably separate water and fat signals in the presence of B0-field inhomogeneity. However, multi-echo methods require longer scan times as compared to single-echo imaging. An accelerated imaging technique is desirable to reduce the length of these methods. This work proposes a new approach for water-fat separation from undersampled data acquisitions. The typical voxel-independent model is generalized to consider estimation of water, fat, field map, and R2* images directly from the undersampled k-space data. Unlike previous works, region-growing is not used for field map estimation.