Bibliografías temáticas / Water/fat imaging / Artículos de revistas

Artículos de revistas sobre el tema "Water/fat imaging"

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Autor: Grafiati
Publicado: 19 de abril de 2023

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1

Bley, Thorsten A., Oliver Wieben, Christopher J. François, Jean H. Brittain y Scott B. Reeder. "Fat and water magnetic resonance imaging". Journal of Magnetic Resonance Imaging 31, n.º 1 (20 de diciembre de 2009): 4–18. http://dx.doi.org/10.1002/jmri.21895.

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2

Xiang, Qing-San y Li An. "Water-fat imaging with direct phase encoding". Journal of Magnetic Resonance Imaging 7, n.º 6 (noviembre de 1997): 1002–15. http://dx.doi.org/10.1002/jmri.1880070612.

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3

Ma, Jingfei. "Dixon techniques for water and fat imaging". Journal of Magnetic Resonance Imaging 28, n.º 3 (septiembre de 2008): 543–58. http://dx.doi.org/10.1002/jmri.21492.

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4

Bauer, Daniel R., Xiong Wang, Jeff Vollin, Hao Xin y Russell S. Witte. "Spectroscopic thermoacoustic imaging of water and fat composition". Applied Physics Letters 101, n.º 3 (16 de julio de 2012): 033705. http://dx.doi.org/10.1063/1.4737414.

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5

Goldfarb, James W. "Fat-water separated delayed hyperenhanced myocardial infarct imaging". Magnetic Resonance in Medicine 60, n.º 3 (septiembre de 2008): 503–9. http://dx.doi.org/10.1002/mrm.21685.

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6

Reeder, Scott B., Charles A. McKenzie, Angel R. Pineda, Huanzhou Yu, Ann Shimakawa, Anja C. Brau, Brian A. Hargreaves, Garry E. Gold y Jean H. Brittain. "Water–fat separation with IDEAL gradient-echo imaging". Journal of Magnetic Resonance Imaging 25, n.º 3 (2007): 644–52. http://dx.doi.org/10.1002/jmri.20831.

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7

Salvati, Roberto, Eric Hitti, Jean-Jacques Bellanger, Hervé Saint-Jalmes y Giulio Gambarota. "Fat ViP MRI: Virtual Phantom Magnetic Resonance Imaging of water–fat systems". Magnetic Resonance Imaging 34, n.º 5 (junio de 2016): 617–23. http://dx.doi.org/10.1016/j.mri.2015.12.002.

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8

SIMON, JACK H. y JERZY SZUMOWSKI. "Proton (Fat/Water) Chemical Shift Imaging in Medical Magnetic Resonance Imaging". Investigative Radiology 27, n.º 10 (octubre de 1992): 865–74. http://dx.doi.org/10.1097/00004424-199210000-00018.

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9

Wiens, Curtis N., Colin M. McCurdy, Jacob D. Willig-Onwuachi y Charles A. McKenzie. "R2*-corrected water-fat imaging using compressed sensing and parallel imaging". Magnetic Resonance in Medicine 71, n.º 2 (8 de marzo de 2013): 608–16. http://dx.doi.org/10.1002/mrm.24699.

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10

Yu, Huanzhou, Scott B. Reeder, Ann Shimakawa, Charles A. McKenzie y Jean H. Brittain. "Robust multipoint water-fat separation using fat likelihood analysis". Magnetic Resonance in Medicine 67, n.º 4 (12 de agosto de 2011): 1065–76. http://dx.doi.org/10.1002/mrm.23087.

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11

Weng, Dehe, Yanli Pan, Xiaodong Zhong y Yan Zhuo. "Water–fat separation with parallel imaging based on BLADE". Magnetic Resonance Imaging 31, n.º 5 (junio de 2013): 656–63. http://dx.doi.org/10.1016/j.mri.2012.10.018.

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12

Keller, P. J., W. W. Hunter y P. Schmalbrock. "Multisection fat-water imaging with chemical shift selective presaturation." Radiology 164, n.º 2 (agosto de 1987): 539–41. http://dx.doi.org/10.1148/radiology.164.2.3602398.

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13

Wang, Dinghui, Nicholas R. Zwart y James G. Pipe. "Joint water-fat separation and deblurring for spiral imaging". Magnetic Resonance in Medicine 79, n.º 6 (5 de octubre de 2017): 3218–28. http://dx.doi.org/10.1002/mrm.26950.

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14

Kaldoudi, Eleni y Steve C. R. Williams. "Fat and water differentiation by nuclear magnetic resonance imaging". Concepts in Magnetic Resonance 4, n.º 1 (enero de 1992): 53–71. http://dx.doi.org/10.1002/cmr.1820040104.

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15

Kaldoudi, Eleni y Steve C. R. Williams. "Fat and water differentiation by nuclear magnetic resonance imaging". Concepts in Magnetic Resonance 4, n.º 2 (abril de 1992): 162–65. http://dx.doi.org/10.1002/cmr.1820040206.

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16

Lu, Minjie, An Jing, Gang Yin, Shiliang Jiang, Qiong Liu, Ning Ma, Tao Zhao, Xiuyu Chen y Shihua Zhao. "MYOCARDIAL FAT DEPOSITION IN DILATED CARDIOMYOPATHY–ASSESSMENT BY USING MR WATER-FAT SEPARATION IMAGING". Heart 98, Suppl 2 (octubre de 2012): E249.3—E250. http://dx.doi.org/10.1136/heartjnl-2012-302920q.8.

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17

Baron, Paul, Roel Deckers, Job G. Bouwman, Chris J. G. Bakker, Martijn de Greef, Max A. Viergever, Chrit T. W. Moonen y Lambertus W. Bartels. "Influence of water and fat heterogeneity on fat‐referenced MR thermometry". Magnetic Resonance in Medicine 75, n.º 3 (marzo de 2016): 1187–97. http://dx.doi.org/10.1002/mrm.25727.

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18

Bachrata, Beata, Bernhard Strasser, Wolfgang Bogner, Albrecht Ingo Schmid, Radim Korinek, Martin Krššák, Siegfried Trattnig y Simon Daniel Robinson. "Simultaneous Multiple Resonance Frequency imaging (SMURF): Fat‐water imaging using multi‐band principles". Magnetic Resonance in Medicine 85, n.º 3 (27 de septiembre de 2020): 1379–96. http://dx.doi.org/10.1002/mrm.28519.

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19

Fellner, Claudia, Marcel Dominik Nickel, Stephan Kannengiesser, Niklas Verloh, Christian Stroszczynski, Michael Haimerl y Lukas Luerken. "Water–Fat Separated T1 Mapping in the Liver and Correlation to Hepatic Fat Fraction". Diagnostics 13, n.º 2 (5 de enero de 2023): 201. http://dx.doi.org/10.3390/diagnostics13020201.

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(1) Background: T1 mapping in magnetic resonance imaging (MRI) of the liver has been proposed to estimate liver function or to detect the stage of liver disease, among others. Thus far, the impact of intrahepatic fat on T1 quantification has only been sparsely discussed. Therefore, the aim of this study was to evaluate the potential of water–fat separated T1 mapping of the liver. (2) Methods: A total of 386 patients underwent MRI of the liver at 3 T. In addition to routine imaging techniques, a 3D variable flip angle (VFA) gradient echo technique combined with a two-point Dixon method was acquired to calculate T1 maps from an in-phase (T1_in) and water-only (T1_W) signal. The results were correlated with proton density fat fraction using multi-echo 3D gradient echo imaging (PDFF) and multi-echo single voxel spectroscopy (PDFF_MRS). Using T1_in and T1_W, a novel parameter FF_T1 was defined and compared with PDFF and PDFF_MRS. Furthermore, the value of retrospectively calculated T1_W (T1_W_calc) based on T1_in and PDFF was assessed. Wilcoxon test, Pearson correlation coefficient and Bland–Altman analysis were applied as statistical tools. (3) Results: T1_in was significantly shorter than T1_W and the difference of both T1 values was correlated with PDFF (R = 0.890). FF_T1 was significantly correlated with PDFF (R = 0.930) and PDFF_MRS (R = 0.922) and yielded only minor bias compared to both established PDFF methods (0.78 and 0.21). T1_W and T1_W_calc were also significantly correlated (R = 0.986). (4) Conclusion: T1_W acquired with a water–fat separated VFA technique allows to minimize the influence of fat on liver T1. Alternatively, T1_W can be estimated retrospectively from T1_in and PDFF, if a Dixon technique is not available for T1 mapping.
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20

Gerdes, Clint M., Richard Kijowski y Scott B. Reeder. "IDEAL Imaging of the Musculoskeletal System: Robust Water–Fat Separation for Uniform Fat Suppression, Marrow Evaluation, and Cartilage Imaging". American Journal of Roentgenology 189, n.º 5 (noviembre de 2007): W284—W291. http://dx.doi.org/10.2214/ajr.07.2593.

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21

Manaster, B. J. "IDEAL Imaging of the Musculoskeletal System: Robust Water–Fat Separation for Uniform Fat Suppression, Marrow Evaluation, and Cartilage Imaging". Yearbook of Diagnostic Radiology 2009 (enero de 2009): 85–86. http://dx.doi.org/10.1016/s0098-1672(09)79325-7.

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22

Wen, Zhifei, Scott B. Reeder, Angel R. Pineda y Norbert J. Pelc. "Noise considerations of three-point water-fat separation imaging methods". Medical Physics 35, n.º 8 (16 de julio de 2008): 3597–606. http://dx.doi.org/10.1118/1.2952644.

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23

Zhadanov, Sergey I., Amish H. Doshi, Puneet S. Pawha, Idoia Corcuera-Solano y Lawrence N. Tanenbaum. "Contrast-Enhanced Dixon Fat-Water Separation Imaging of the Spine". Journal of Computer Assisted Tomography 40, n.º 6 (2016): 985–90. http://dx.doi.org/10.1097/rct.0000000000000453.

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24

Yu, Huanzhou, Scott B. Reeder, Charles A. McKenzie, Anja C. S. Brau, Ann Shimakawa, Jean H. Brittain y Norbert J. Pelc. "Single acquisition water-fat separation: Feasibility study for dynamic imaging". Magnetic Resonance in Medicine 55, n.º 2 (febrero de 2006): 413–22. http://dx.doi.org/10.1002/mrm.20771.

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25

Börnert, Peter, Jochen Keupp, Holger Eggers y Bernd Aldefeld. "Whole-body 3D water/fat resolved continuously moving table imaging". Journal of Magnetic Resonance Imaging 25, n.º 3 (2007): 660–65. http://dx.doi.org/10.1002/jmri.20861.

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26

Alanen, A., M. Komu, R. Leino y S. Toikkanen. "MR and magnetisation transfer imaging in cirrhotic and fatty livers". Acta Radiologica 39, n.º 4 (julio de 1998): 434–39. http://dx.doi.org/10.1080/02841859809172459.

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Purpose: To determine whether low-field MR fat/water separation and magnetisation transfer (MT) techniques are useful in studying the livers of patients with parenchymal liver diseases in vivo. Material and Methods: MR and MT imaging of the liver in 33 patients (14 with primary biliary cirrhosis, 15 with alcohol-induced liver disease, and 4 with fatty liver) was performed by means of the fat/water separation technique at 0.1 T. The relaxation time T1 and the MT contrast (MTC) parameter of liver and spleen tissue were measured, and the relative proton density fat content N(%) and MTC of the liver were calculated from the separate fat and water images. The value of N(%) was also compared with the percentage of fatty hepatocytes at histology. Results: The relaxation rate R1 of liver measured from the magnitude image, and the difference in the value of MTC measured from the water image compared with the one measured from the fat and water magnitude image, both depended linearly on the value of N(%). The value of N(%) correlated significantly with the percentage of the fatty hepatocytes. In in vivo fatty tissue, fat infiltration increased both the observed relaxation rate R1 and the measured magnetisation ratio (the steady state magnetisation Ms divided by the equilibrium magnetisation Mo, Ms/Mo) and consequently decreased the MT efficiency measured in a magnitude MR image. The amount of liver fibrosis did not correlate with the value of MTC measured after fat separation. Conclusion: Our results in studying fatty livers with MR imaging and the MT method show that the fat/water separation gives more reliable parametric results. Characterisation of liver cirrhosis by means of the MTC parameter is not reliable, even after fat separation.
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27

Yu, Huanzhou, Ann Shimakawa, Charles A. McKenzie, Ethan Brodsky, Jean H. Brittain y Scott B. Reeder. "Multiecho water-fat separation and simultaneousR2* estimation with multifrequency fat spectrum modeling". Magnetic Resonance in Medicine 60, n.º 5 (noviembre de 2008): 1122–34. http://dx.doi.org/10.1002/mrm.21737.

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28

de Vrijer, Barbra, Stephanie Giza, Craig Olmstead, Debbie Penava, Genevieve Eastabrook, Timothy Regnault y Charles McKenzie. "O-OBS-MFM-MD-070 Imaging Fetal Subcutaneous Fat Development Using 3D Water-Fat MRI". Journal of Obstetrics and Gynaecology Canada 39, n.º 5 (mayo de 2017): 387. http://dx.doi.org/10.1016/j.jogc.2017.03.020.

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29

Peterson, Pernilla, Thobias Romu, Håkan Brorson, Olof Dahlqvist Leinhard y Sven Månsson. "Fat quantification in skeletal muscle using multigradient-echo imaging: Comparison of fat and water references". Journal of Magnetic Resonance Imaging 43, n.º 1 (10 de junio de 2015): 203–12. http://dx.doi.org/10.1002/jmri.24972.

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30

Jaubert, Olivier, Gastão Cruz, Aurélien Bustin, Torben Schneider, Begoña Lavin, Peter Koken, Reza Hajhosseiny et al. "Water–fat Dixon cardiac magnetic resonance fingerprinting". Magnetic Resonance in Medicine 83, n.º 6 (18 de noviembre de 2019): 2107–23. http://dx.doi.org/10.1002/mrm.28070.

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31

Reeder, Scott B., Brian A. Hargreaves, Huanzhou Yu y Jean H. Brittain. "Homodyne reconstruction and IDEAL water-fat decomposition". Magnetic Resonance in Medicine 54, n.º 3 (2005): 586–93. http://dx.doi.org/10.1002/mrm.20586.

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32

Wu, Yan, Marcus Alley, Zhitao Li, Keshav Datta, Zhifei Wen, Christopher Sandino, Ali Syed et al. "Deep Learning-Based Water-Fat Separation from Dual-Echo Chemical Shift-Encoded Imaging". Bioengineering 9, n.º 10 (19 de octubre de 2022): 579. http://dx.doi.org/10.3390/bioengineering9100579.

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Conventional water–fat separation approaches suffer long computational times and are prone to water/fat swaps. To solve these problems, we propose a deep learning-based dual-echo water–fat separation method. With IRB approval, raw data from 68 pediatric clinically indicated dual echo scans were analyzed, corresponding to 19382 contrast-enhanced images. A densely connected hierarchical convolutional network was constructed, in which dual-echo images and corresponding echo times were used as input and water/fat images obtained using the projected power method were regarded as references. Models were trained and tested using knee images with 8-fold cross validation and validated on out-of-distribution data from the ankle, foot, and arm. Using the proposed method, the average computational time for a volumetric dataset with ~400 slices was reduced from 10 min to under one minute. High fidelity was achieved (correlation coefficient of 0.9969, l1 error of 0.0381, SSIM of 0.9740, pSNR of 58.6876) and water/fat swaps were mitigated. I is of particular interest that metal artifacts were substantially reduced, even when the training set contained no images with metallic implants. Using the models trained with only contrast-enhanced images, water/fat images were predicted from non-contrast-enhanced images with high fidelity. The proposed water–fat separation method has been demonstrated to be fast, robust, and has the added capability to compensate for metal artifacts.
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33

Chang, Jerry S., Bachir Taouli, Nouha Salibi, Elizabeth M. Hecht, Deanna G. Chin y Vivian S. Lee. "Opposed-Phase MRI for Fat Quantification in Fat-Water Phantoms with 1H MR Spectroscopy to Resolve Ambiguity of Fat or Water Dominance". American Journal of Roentgenology 187, n.º 1 (julio de 2006): W103—W106. http://dx.doi.org/10.2214/ajr.05.0695.

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34

Borrello, Joseph A., Dorit D. Adler y W. Richard Dunham. "MR IMAGING OF THE BREAST USING A DEDICATED BREAST COIL AND WATER-FAT IMAGING". Investigative Radiology 24, n.º 12 (diciembre de 1989): S132. http://dx.doi.org/10.1097/00004424-198912000-00236.

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35

Goldfarb, James W. y Sheeba Arnold-Anteraper. "Water-fat separation imaging of the heart with standard magnetic resonance bSSFP CINE imaging". Magnetic Resonance in Medicine 71, n.º 6 (31 de julio de 2013): 2096–104. http://dx.doi.org/10.1002/mrm.24879.

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36

Kim, Hokun, Joon-Il Choi y Hyun-Soo Lee. "Friend or Foe: How to Suppress and Measure Fat During Abdominal Resonance Imaging?" Korean Journal of Abdominal Radiology 6, n.º 1 (15 de julio de 2022): 22–36. http://dx.doi.org/10.52668/kjar.2022.00143.

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The suppression of fat signals in abdominal magnetic resonance imaging has become a basic and routine practice in the diagnosis of pathologic conditions of abdominal organs in clinical settings. Many fat-suppression techniques have been developed in the past several decades, with fat-quantification methods introduced in response in more recent years. Fat-suppression techniques can be divided into two categories. Chemical shift–based techniques include chemical shift selective (CHESS), water excitation, and the Dixon method. CHESS is the most commonly used fat-suppression method, nulling the fat signal using a fat-selective radiofrequency pulse with a spoiler gradient. Water excitation employs a binomial pulse that excites only the water protons. Finally, the Dixon method involves using the in-phase/out-of-phase cycling of fat and water. An inversionbased technique, known as short tau inversion recovery (STIR), uses a pre-excitation inversion pulse that inverts the spin of all tissues. By selecting the appropriate MRI inversion time such that the longitudinal magnetization of fat is zero, fat protons will not contribute to the MRI signal. Also, spectral attenuated inversion recovery (SPAIR) is a hybrid technique that combines the characteristics of both CHESS and STIR. The most precise fat-quantification technique known to date is a complex-based multipoint Dixon method, with which the protondensity fat fraction (PDFF) can be obtained. Multiple confounding factors must be well-corrected for accurate fat quantification. Radiologists should be familiar with the various fat suppression and measurement methods during MRI and be able to apply them to enhance patient care.
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37

Chebrolu, Venkata V., Catherine D. G. Hines, Huanzhou Yu, Angel R. Pineda, Ann Shimakawa, Charles A. McKenzie, Alexey Samsonov, Jean H. Brittain y Scott B. Reeder. "Independent estimation ofT*2for water and fat for improved accuracy of fat quantification". Magnetic Resonance in Medicine 63, n.º 4 (mayo de 2010): 849–57. http://dx.doi.org/10.1002/mrm.22300.

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38

SCHICK, FRITZ, STEPHAN MILLER, ULRICH HAHN, THOMAS NÄGELE, UWE HELBER, NORBERT STAUDER, KLAUS BRECHTEL y CLAUS D. CLAUSSEN. "Fat- and Water-Selective MR Cine Imaging of the Human Heart". Investigative Radiology 35, n.º 5 (mayo de 2000): 311–18. http://dx.doi.org/10.1097/00004424-200005000-00005.

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39

Jackson, A., S. Sheppard, R. D. Laitt, A. Kassner y D. Moriarty. "Optic neuritis: MR imaging with combined fat- and water-suppression techniques." Radiology 206, n.º 1 (enero de 1998): 57–63. http://dx.doi.org/10.1148/radiology.206.1.9423652.

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40

Nezafat, Maryam, Shiro Nakamori, Tamer A. Basha, Ahmed S. Fahmy, Thomas Hauser y René M. Botnar. "Imaging sequence for joint myocardial T1 mapping and fat/water separation". Magnetic Resonance in Medicine 81, n.º 1 (29 de julio de 2018): 486–94. http://dx.doi.org/10.1002/mrm.27390.

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41

Glover, Gary H. "Multipoint dixon technique for water and fat proton and susceptibility imaging". Journal of Magnetic Resonance Imaging 1, n.º 5 (septiembre de 1991): 521–30. http://dx.doi.org/10.1002/jmri.1880010504.

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42

Farrelly, Cormac, Saurabh Shah, Amir Davarpanah, Aoife N. Keeling y James C. Carr. "ECG-Gated Multiecho Dixon Fat-Water Separation in Cardiac MRI: Advantages Over Conventional Fat-Saturated Imaging". American Journal of Roentgenology 199, n.º 1 (julio de 2012): W74—W83. http://dx.doi.org/10.2214/ajr.11.7759.

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43

Goldfarb, James W., Marguerite Roth y Jing Han. "Myocardial Fat Deposition after Left Ventricular Myocardial Infarction: Assessment by Using MR Water-Fat Separation Imaging". Radiology 253, n.º 1 (octubre de 2009): 65–73. http://dx.doi.org/10.1148/radiol.2532082290.

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44

Abbott, Rebecca, Anneli Peolsson, Janne West, James M. Elliott, Ulrika Åslund, Anette Karlsson y Olof Dahlqvist Leinhard. "The qualitative grading of muscle fat infiltration in whiplash using fat and water magnetic resonance imaging". Spine Journal 18, n.º 5 (mayo de 2018): 717–25. http://dx.doi.org/10.1016/j.spinee.2017.08.233.

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45

Liu, Chia-Ying, Alban Redheuil, Ronald Ouwerkerk, Joao A. C. Lima y David A. Bluemke. "Myocardial fat quantification in humans: Evaluation by two-point water-fat imaging and localized proton spectroscopy". Magnetic Resonance in Medicine 63, n.º 4 (abril de 2010): 892–901. http://dx.doi.org/10.1002/mrm.22289.

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46

Manabe, Atsutaka, Toshiyuki Miyazaki y Hideo Toyoshima. "0.1-T human fat/water separation by SIDAC". Magnetic Resonance in Medicine 5, n.º 5 (noviembre de 1987): 492–501. http://dx.doi.org/10.1002/mrm.1910050513.

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47

Wu, Hochong H., Jin Hyung Lee y Dwight G. Nishimura. "Fat/water separation using a concentric rings trajectory". Magnetic Resonance in Medicine 61, n.º 3 (18 de diciembre de 2008): 639–49. http://dx.doi.org/10.1002/mrm.21865.

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48

Johnson, Kevin M., Oliver Wieben y Alexey A. Samsonov. "Phase-contrast velocimetry with simultaneous fat/water separation". Magnetic Resonance in Medicine 63, n.º 6 (23 de abril de 2010): 1564–74. http://dx.doi.org/10.1002/mrm.22355.

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49

Taviani, Valentina, Diego Hernando, Christopher J. Francois, Ann Shimakawa, Karl K. Vigen, Scott K. Nagle, Mark L. Schiebler, Thomas M. Grist y Scott B. Reeder. "Whole-heart chemical shift encoded water-fat MRI". Magnetic Resonance in Medicine 72, n.º 3 (1 de noviembre de 2013): 718–25. http://dx.doi.org/10.1002/mrm.24982.

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50

Marty, Benjamin y Pierre G. Carlier. "MR fingerprinting for water T1 and fat fraction quantification in fat infiltrated skeletal muscles". Magnetic Resonance in Medicine 83, n.º 2 (10 de septiembre de 2019): 621–34. http://dx.doi.org/10.1002/mrm.27960.

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