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Multi‐scale graph‐cut algorithm for efficient water‐fat separation
Author(s) -
Berglund Johan,
Skorpil Mikael
Publication year - 2017
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.26479
Subject(s) - robustness (evolution) , algorithm , computer science , computation , graph , voxel , quadratic equation , noise (video) , artificial intelligence , mathematics , theoretical computer science , image (mathematics) , gene , biochemistry , chemistry , geometry
Purpose To improve the accuracy and robustness to noise in water‐fat separation by unifying the multiscale and graph cut based approaches to B 0 ‐correction. Methods A previously proposed water‐fat separation algorithm that corrects for B 0 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