Reeder SB, Cruite I, Hamilton G, Sirlin CB (2011) Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy. J Magn Reson Imaging 34(4):729–749. https://doi.org/10.1002/jmri.22580

Article  PubMed  PubMed Central  Google Scholar 

Yu H, Shimakawa A, McKenzie CA, Brodsky E, Brittain JH, Reeder SB (2008) Multiecho water–fat separation and simultaneous R2* estimation with multifrequency fat spectrum modeling. Magn Reson Med 60(5):1122–1134. https://doi.org/10.1002/mrm.21737

Article  PubMed  PubMed Central  Google Scholar 

Thomas EL, Fitzpatrick JA, Malik SJ, Taylor-Robinson SD, Bell JD (2013) Whole body fat: content and distribution. Prog Nucl Magn Reson Spectrosc 73:56–80. https://doi.org/10.1016/j.pnmrs.2013.04.001

Article  CAS  PubMed  Google Scholar 

Park HW, Cho ZH (1986) High-resolution human in vivo spectroscopic imaging using echo- time encoding technique. Magn Reson Med 3(3):448–453. https://doi.org/10.1002/mrm.1910030310

Article  CAS  PubMed  Google Scholar 

Dixon WT (1984) Simple proton spectroscopic imaging. Radiology 153(1):189–194. https://doi.org/10.1148/radiology.153.1.6089263

Article  CAS  PubMed  Google Scholar 

Tsao J, Jiang Y (2013) Hierarchical IDEAL: fast, robust, and multiresolution separation of multiple chemical species from multiple echo times. Magn Reson Med 70(1):155–159. https://doi.org/10.1002/mrm.24441

Article  PubMed  Google Scholar 

Zhong X, Nickel MD, Kannengiesser SAR, Dale BM, Kiefer B, Bashir MR (2014) Liver fat quantification using a multi-step adaptive fitting approach with multi-echo GRE imaging: liver fat quantification with adaptive fitting. Magn Reson Med 72(5):1353–1365. https://doi.org/10.1002/mrm.25054

Article  PubMed  Google Scholar 

Diefenbach MN, Ruschke S, Eggers H, Meineke J, Rummeny EJ, Karampinos DC (2018) Improving chemical shift encoding-based water–fat separation based on a detailed consideration of magnetic field contributions. Magn Reson Med 80(3):990–1004. https://doi.org/10.1002/mrm.27097

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hernando D, Kellman P, Haldar JP, Liang Z-P (2009) Robust water/fat separation in the presence of large field inhomogeneities using a graph cut algorithm. Magn Reson Med. https://doi.org/10.1002/mrm.22177

Article  PubMed  PubMed Central  Google Scholar 

Dong J et al (2015) Simultaneous phase unwrapping and removal of chemical shift (SPURS) using graph cuts: application in quantitative susceptibility mapping. IEEE Trans Med Imaging 34(2):531–540. https://doi.org/10.1109/TMI.2014.2361764

Article  PubMed  Google Scholar 

Reeder SB et al (2004) Multicoil Dixon chemical species separation with an iterative least-squares estimation method. Magn Reson Med 51(1):35–45. https://doi.org/10.1002/mrm.10675

Article  CAS  PubMed  Google Scholar 

Sharma SD, Artz NS, Hernando D, Horng DE, Reeder SB (2015) Improving chemical shift encoded water–fat separation using object-based information of the magnetic field inhomogeneity. Magn Reson Med 73(2):597–604. https://doi.org/10.1002/mrm.25163

Article  PubMed  Google Scholar 

Goldfarb JW, Craft J, Cao JJ (2019) Water–fat separation and parameter mapping in cardiac MRI via deep learning with a convolutional neural network: MR water–fat separation. J Magn Reson Imaging 50(2):655–665. https://doi.org/10.1002/jmri.26658

Article  PubMed  Google Scholar 

Rumelhart DE, Hinton GE, Williams RJ (1986) Learning representations by back-propagating errors. Nature 323(6088):533–536. https://doi.org/10.1038/323533a0

Article  Google Scholar 

Shih S-F, Kafali SG, Armstrong T, Zhong X, Calkins KL, Wu HH (2021) Deep learning-based parameter mapping with uncertainty estimation for fat quantification using accelerated free-breathing radial MRI. In: 2021 IEEE 18th international symposium on biomedical imaging (ISBI), Nice, France: IEEE, Apr 2021, pp 433–437. https://doi.org/10.1109/ISBI48211.2021.9433938

Cho J, Park H (2019) Robust water–fat separation for multi-echo gradient-recalled echo sequence using convolutional neural network. Magn Reson Med 82(1):476–484. https://doi.org/10.1002/mrm.27697

Article  PubMed  Google Scholar 

Shen C, She H, Du Y (Nov 2020) Improved robustness in water–fat separation in MRI using conditional adversarial networks. In: 2020 7th international conference on biomedical and bioinformatics engineering. ACM, Kyoto, Japan, pp 31–35. https://doi.org/10.1145/3444884.3444891

Andersson J, Ahlström H, Kullberg J (2019) Separation of water and fat signal in whole-body gradient echo scans using convolutional neural networks. Magn Reson Med 82(3):1177–1186. https://doi.org/10.1002/mrm.27786

Article  PubMed  PubMed Central  Google Scholar 

Liang X, Nguyen D, Jiang SB (2021) Generalizability issues with deep learning models in medicine and their potential solutions: illustrated with cone-beam computed tomography (CBCT) to computed tomography (CT) image conversion. Mach Learn Sci Technol 2(1):015007. https://doi.org/10.1088/2632-2153/abb214

Article  Google Scholar 

Krois J et al (2021) Generalizability of deep learning models for dental image analysis. Sci Rep 11(1):6102. https://doi.org/10.1038/s41598-021-85454-5

Article  CAS  PubMed  PubMed Central  Google Scholar 

Jafari R et al (2021) Deep neural network for water/fat separation: supervised training, unsupervised training, and no training. Magn Reson Med 85(4):2263–2277. https://doi.org/10.1002/mrm.28546

Article  PubMed  Google Scholar 

Cole E, Cheng J, Pauly J, Vasanawala S (2021) Analysis of deep complex-valued convolutional neural networks for MRI reconstruction and phase-focused applications. Magn Reson Med 86(2):1093–1109. https://doi.org/10.1002/mrm.28733

Article  PubMed  PubMed Central  Google Scholar 

Hu HH et al (2012) ISMRM workshop on fat–water separation: insights, applications and progress in MRI. Magn Reson Med 68(2):378–388. https://doi.org/10.1002/mrm.24369

Article  PubMed  PubMed Central  Google Scholar 

Meneses JP et al (2023) Liver PDFF estimation using a multi-decoder water–fat separation neural network with a reduced number of echoes. Eur Radiol 33(9):6557–6568. https://doi.org/10.1007/s00330-023-09576-2

Article  PubMed  PubMed Central  Google Scholar 

Soliman AS (2014) Acquisition and reconstruction techniques for fat quantification using magnetic resonance imaging. The University of Western Ontario, Canada

Kingma DP, Ba J (2024) Adam: a method for stochastic optimization. Jan 29, 2017. arXiv:1412.6980. Accessed: Jan 04, 2024 (Online). Available: http://arxiv.org/abs/1412.6980

Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612. https://doi.org/10.1109/TIP.2003.819861

Article  PubMed  Google Scholar 

Eggers H, Börnert P (2014) Chemical shift encoding-based water–fat separation methods. J Magn Reson Imaging 40(2):251–268. https://doi.org/10.1002/jmri.24568

Article  PubMed  Google Scholar 

Hernando D, Hines CDG, Yu H, Reeder SB (2012) Addressing phase errors in fat–water imaging using a mixed magnitude/complex fitting method. Magn Reson Med 67(3):638–644. https://doi.org/10.1002/mrm.23044

Article  CAS  PubMed  Google Scholar 

Yu H et al (2011) Combination of complex-based and magnitude-based multiecho water–fat separation for accurate quantification of fat-fraction. Magn Reson Med 66(1):199–206. https://doi.org/10.1002/mrm.22840

Article  PubMed  PubMed Central  Google Scholar 

Yu H, Reeder SB, Shimakawa A, Brittain JH, Pelc NJ (2005) Field map estimation with a region growing scheme for iterative 3-point water–fat decomposition. Magn Reson Med 54(4):1032–1039. https://doi.org/10.1002/mrm.20654

Article  PubMed  Google Scholar 

Yu H et al (2007) Multiecho reconstruction for simultaneous water–fat decomposition and T2* estimation. J Magn Reson Imaging 26(4):1153–1161. https://doi.org/10.1002/jmri.21090

Article  PubMed  Google Scholar 

Roberts NT, Hernando D, Panagiotopoulos N, Reeder SB (2022) Addressing concomitant gradient phase errors in time-interleaved chemical shift-encoded MRI fat fraction and R2* mapping with a pass-specific phase fitting method. Magn Reson Med 87(6):2826–2838. https://doi.org/10.1002/mrm.29175

Article  CAS  PubMed