TY - JOUR
T1 - Algebraic decomposition of fat and water in MRI
AU - Jacob, Mathews
AU - Sutton, Bradley P.
N1 - Funding Information:
This work was supported by the Beckman Foundation and the startup funds at the University of Rochester. The authors would like to thank Prof. J. Fessler and H. Wonseok at the University of Michigan at Ann Arbor for providing the region-merging IDEAL code, which was modified for the comparisons. The authors would also like to thank the anonymous reviewers, whose comments significantly improved the paper.
PY - 2009/2
Y1 - 2009/2
N2 - The decomposition of magnetic resonance imaging (MRI) data to generate water and fat images has several applications in medical imaging, including fat suppression and quantification of visceral fat. We introduce a novel algorithm to overcome some of the problems associated with current analytical and iterative decomposition schemes. In contrast to traditional analytical schemes, our approach is general enough to accommodate any uniform echo-shift pattern, any number of metabolites and signal samples. In contrast to region-growing method that use a smooth field-map initialization to resolve the ambiguities with the IDEAL algorithm, we propose to use an explicit smoothness constraint on the final fieldmap estimate. Towards this end, we estimate the number of feasible solutions at all the voxels, prior to the evaluation of the roots. This approach enables the algorithm to evaluate all the feasible roots, thus avoiding the convergence to the wrong solution. The estimation procedure is based on a modification of the harmonic retrieval (HR) framework to account for the chemical shift dependence in the frequencies. In contrast to the standard linear HR framework, we obtain the frequency shift as the common root of a set of quadratic equations. On most of the pixels with multiple feasible solutions, the correct solution can be identified by a simple sorting of the solutions. We use a region-merging algorithm to resolve the remaining ambiguity and phase-wrapping. Experimental results indicate that the proposed algebraic scheme eliminates most of the difficulties with the current schemes, without compromising the noise performance. Moreover, the proposed algorithm is also computationally more efficient.
AB - The decomposition of magnetic resonance imaging (MRI) data to generate water and fat images has several applications in medical imaging, including fat suppression and quantification of visceral fat. We introduce a novel algorithm to overcome some of the problems associated with current analytical and iterative decomposition schemes. In contrast to traditional analytical schemes, our approach is general enough to accommodate any uniform echo-shift pattern, any number of metabolites and signal samples. In contrast to region-growing method that use a smooth field-map initialization to resolve the ambiguities with the IDEAL algorithm, we propose to use an explicit smoothness constraint on the final fieldmap estimate. Towards this end, we estimate the number of feasible solutions at all the voxels, prior to the evaluation of the roots. This approach enables the algorithm to evaluate all the feasible roots, thus avoiding the convergence to the wrong solution. The estimation procedure is based on a modification of the harmonic retrieval (HR) framework to account for the chemical shift dependence in the frequencies. In contrast to the standard linear HR framework, we obtain the frequency shift as the common root of a set of quadratic equations. On most of the pixels with multiple feasible solutions, the correct solution can be identified by a simple sorting of the solutions. We use a region-merging algorithm to resolve the remaining ambiguity and phase-wrapping. Experimental results indicate that the proposed algebraic scheme eliminates most of the difficulties with the current schemes, without compromising the noise performance. Moreover, the proposed algorithm is also computationally more efficient.
KW - Fat-water decomposition
KW - Harmonic retrieval
KW - Linear prediction
KW - Magnetic resonance imaging (MRI)
KW - Sylvester matrix
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U2 - 10.1109/TMI.2008.927344
DO - 10.1109/TMI.2008.927344
M3 - Article
C2 - 19188106
AN - SCOPUS:59449094173
SN - 0278-0062
VL - 28
SP - 173
EP - 184
JO - IEEE transactions on medical imaging
JF - IEEE transactions on medical imaging
IS - 2
M1 - 4556618
ER -