Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
470-04-104 ISMRM Abstract

Echo-dependent Flip Angle acquisition and Physics-informed Deep Learning reconstruction for high-resolution fat-water imaging

Primary: Acquisition & Reconstruction - Image Reconstruction: AI
Secondary: Acquisition & Reconstruction - Quantitative Imaging: chest, abdomen, and pelvis
470-04-104 · Fat-Water Separation and Fat Suppression · Tuesday, 12 May, 9:15 AM–10:10 AM · Traditional Posters | Exhibition Hall
Keywords: Fat and Fat/Water Separation Quantitative Imaging High-Resolution MRI Multi-echo GRE
Accepted
Moorthy Ganeshkumar1, Devasenathipathy Kandasamy2, Esha Baidya Kayal1, Amit Mehndiratta1,3,4
1Centre for Biomedical Engineering, Indian Institute of Technology, Delhi, India
2Department of Radio Diagnosis, All India Institute of Medical Sciences, New Delhi, India
3Yardi School of Artificial Intelligence, Indian Institute of Technology, Delhi, India
4The University of New South Wales, Sydney, Australia
Presenting Author: Priyanka Bhat

Synopsis

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References

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2. D. Hernando, Z. Liang, and P. Kellman, “Chemical shift–based water/fat separation: A comparison of signal models,” Magn. Reson. Med., vol. 64, no. 3, pp. 811–822, Sep. 2010, doi: 10.1002/mrm.22455. [doi]
3. P. Daudé et al., “Comparative review of algorithms and methods for chemical‐shift‐encoded quantitative fat‐water imaging,” Magn. Reson. Med., vol. 91, no. 2, pp. 741–759, Feb. 2024, doi: 10.1002/mrm.29860. [doi]
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6. R. Jafari et al., “Deep neural network for water/fat separation: Supervised training, unsupervised training, and no training,” Magn. Reson. Med., vol. 85, no. 4, pp. 2263–2277, Apr. 2021, doi: 10.1002/mrm.28546. [doi]
7. D. Hernando, P. Kellman, J. P. Haldar, and Z.-P. Liang, “Robust water/fat separation in the presence of large field inhomogeneities using a graph cut algorithm,” Magn. Reson. Med., p. NA-NA, 2009, doi: 10.1002/mrm.22177. [doi]

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http://echo.ismrm.org/p/ISMRM2026/470-04-104