Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
351-03-006 / 351-03-006 ISMRM Abstract

Accelerated 3D dual-echo MRI with Cross-Attention-Guided Joint Optimization of Sampling and Reconstruction

Primary: Acquisition & Reconstruction - Image Reconstruction: AI
Secondary: Acquisition & Reconstruction - AI methods
351-03-006 · AI Methods · Monday, 11 May, 4:10 PM–5:46 PM · Power Pitch Theatre 1
351-03-006 · AI Methods · Monday, 11 May, 4:10 PM–5:46 PM · Power Pitch Theatre 1
Keywords: Sampling pattern optimization Deep learning Dual echo Deep-learning-based image reconstruction
Accepted
Aiqi Sun1, Cagan Alkan2, Marcus Alley1, Yan Wu1, Ali B Syed1, John Pauly2, Daniel B Ennis1,3,4,5, Shreyas Vasanawala1
1Department of Radiology, Stanford University, Stanford, United States of America
2Department of Electrical Engineering, Stanford University, Stanford, United States of America
3Department of Bioengineering, Stanford University, Stanford, United States of America
4Cardiovascular Institute, Stanford University, Stanford, United States of America
5Division of Radiology, Veterans Administration Health Care System, Palo Alto, United States of America
Presenting Author: Chenwei Tang

Synopsis

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References

1. Eggers H, Brendel B, Duijndam A, and Herigault G. Dual-echo Dixon imaging with flexible choice of echo times. Magn Reson Med. 2011;65(1):96-107. DOI: 10.1002/mrm.22578 [doi]
2. Zhang T, Chen Y, Bao S, Alley MT, Pauly JM, Hargreaves BA, and Vasanawala SS. Resolving phase ambiguity in dual-echo Dixon imaging using a projected power method. Magn Reson Med. 2017;77(5):2066-2076. DOI: 10.1002/mrm.26287 [doi]
3. Weiss T, Senouf O, Vedula S, Michailovich O, Zibulevsky M, and Bronstein A. PILOT: Physics-informed learned optimized trajectories for accelerated MRI. arXiv:1909.05773, 2019.
4. Aggarwal HK and Jacob M. J-MoDL: Joint model-based deep learning for optimized sampling and reconstruction. IEEE J. Sel. Top. Signal Process. 2020;14(6):1151–1162. DOI: 10.1109/jstsp.2020.3004094 [doi]
5. Wang G, Luo T, Nielsen JF, Noll DC, and Fessler JA. B-spline parameterized joint optimization of reconstruction and k-space trajectories (BJORK) for accelerated 2D MRI. IEEE Trans Med Imaging. 2022;41(9):2318–2330. DOI: 10.1109/TMI.2022.3161875 [doi]
6. Alkan C, Mardani M, Liao C, Li Z, Vasanawala SS, and Pauly JM. AutoSamp: Autoencoding k-space sampling via variational information maximization for 3D MRI. IEEE Trans Med Imaging. 2024;44(1):270-283. DOI: 10.1109/TMI.2024.3443292 [doi]
7. Sun A, Alkan C, Alley M, Wu Y, Zhang C, Syed A, Pauly JM, Ennis D, and Vasanawala SS. Joint optimization of sampling pattern and image reconstruction for 3D dual-echo spoiled gradient echo MRI. Proceedings of 2025 ISMRM & ISMRT Annual Meeting & Exhibition, Honolulu, Hawai’i. 2025;p1368.
8. Uecker M, Lai P, Murphy MJ, Virtue P, Elad M, Pauly JM, Vasanawala SS, Lustig M. ESPIRiT--an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA. Magn Reson Med. 2014;71(3):990-1001. DOI: 10.1002/mrm.24751 [doi]
9. Zhang T, Pauly JM, Vasanawala SS, and Lustig M. Coil compression for accelerated imaging with Cartesian sampling. Magn Reson Med. 2013;69(2):571-82. DOI: 10.1002/mrm.24267 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/351-03-006