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. 2008 Mar;59(3):571-80.
doi: 10.1002/mrm.21522.

Joint estimation of water/fat images and field inhomogeneity map

D Hernando  1 , J P Haldar, B P Sutton, J Ma, P Kellman, Z-P Liang
Affiliations

Joint estimation of water/fat images and field inhomogeneity map

D Hernando et al. Magn Reson Med. 2008 Mar.

Abstract

Water/fat separation in the presence of B 0 field inhomogeneity is a problem of considerable practical importance in MRI. This article describes two complementary methods for estimating the water/fat images and the field inhomogeneity map from Dixon-type acquisitions. One is based on variable projection (VARPRO) and the other on linear prediction (LP). The VARPRO method is very robust and can be used in low signal-to-noise ratio conditions because of its ability to achieve the maximum-likelihood solution. The LP method is computationally more efficient, and is shown to perform well under moderate levels of noise and field inhomogeneity. These methods have been extended to handle multicoil acquisitions by jointly solving the estimation problem for all the coils. Both methods are analyzed and compared and results from several experiments are included to demonstrate their performance.

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Figures

FIG. 1
FIG. 1
Comparison between theoretical bounds (CRLB) and empirical MSE for amplitude estimation. The solid line indicates the CRLB, while the circles and asterisks represent the empirical results obtained from VARPRO and LP, respectively.
FIG. 2
FIG. 2
Quantitative comparison of IDEAL, VARPRO, and LP for water/fat decomposition including spatial smoothness constraints on the field map. Relative errors are shown for water image reconstruction using the three methods, for different levels of field inhomogeneity, and averaged for three different synthetic datasets.
FIG. 3
FIG. 3
Water/fat decomposition from a brain acquisition. The first column contains the estimated water component using the different algorithms. The second column contains the estimated fat component. The third column contains the regularized field map. (a–c) IDEAL estimates. The smooth field map is obtained by filtering the raw field map (resulting from voxel-by-voxel estimation) with a smoothing kernel (3); (d–f) VARPRO estimates. The smooth field map is obtained directly by applying an MRF prior; (g–i) LP estimates. The smooth field map is obtained by weighted LS regularization of the raw field map.
FIG. 4
FIG. 4
Water/fat decomposition from a multicoil abdominal acquisition. The first column contains the estimated water component using the different algorithms. The second column contains the estimated fat component. Both components are displayed using sum of squares combination of the multicoil signal. The third column contains the regularized field map. (a–c) VARPRO estimates using all six echo time shifts; (d–f) VARPRO estimates using three water/fat shifts; (g–i) LP estimates using three water/fat shifts.
FIG. 5
FIG. 5
Comparison of IDEAL and VARPRO results in the presence of high field inhomogeneity. (a–c) IDEAL estimates for water, fat, and field map, respectively; (d–f) VARPRO estimates for water, fat, and field map, respectively.
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References

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