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Multi-scale graph-cut algorithm for efficient water-fat separation
Johan Berglund1,2, Mikael Skorpil3,4
1Department of Medical Radiation Physics, Karolinska University Hospital, Stockholm, Sweden.
Purpose:
To improve the accuracy and robustness to noise in water-fat separation by unifying the multiscale and graph cut based approaches to B0 -correction.
Methods:
A previously proposed water-fat separation algorithm that corrects for B0 field inhomogeneity in 3D by a single quadratic pseudo-Boolean optimization (QPBO) graph cut was incorporated into a multi-scale framework, where field map solutions are propagated from coarse to fine scales for voxels that are not resolved by the graph cut. The accuracy of the single-scale and multi-scale QPBO algorithms was evaluated against benchmark reference datasets. The robustness to noise was evaluated by adding noise to the input data prior to water-fat separation.
Results:
Both algorithms achieved the highest accuracy when compared with seven previously published methods, while computation times were acceptable for implementation in clinical routine. The multi-scale algorithm was more robust to noise than the single-scale algorithm, while causing only a small increase (+10%) of the reconstruction time.
Conclusion:
The proposed 3D multi-scale QPBO algorithm offers accurate water-fat separation, robustness to noise, and fast reconstruction. The software implementation is freely available to the research community. Magn Reson Med 78:941-949, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
