552-02-017 / 552-02-017 ISMRM Abstract

Synthetic DENSE Data Generation Using Physics-Based Simulation and Conditional DDPM for Improved Echo Suppression

Primary: Acquisition & Reconstruction - AI methods

Secondary: Cardiovascular - Myocardium

552-02-017 · Quantitative Imaging: Relaxometry, Multiparametric, MR Fingerprinting, and Synthetic MRI · Wednesday, 13 May, 1:40 PM–3:16 PM · Power Pitch Theatre 2

Keywords: Artifacts correction Image synthesis DENSE Synthetic Data Generation DENSE Strain

Accepted

Yuxiao Wu^1,2, Shu-Fu Shih ¹, Jun Lyu¹, Tengyue Zhang^1,2, Siyue Li¹, Sile Wang^1,2, Kim-Lien Nguyen^1,2,3, Xiaodong Zhong^1,2

¹David Geffen School of Medicine, University of California Los Angeles, Los Angeles, United States of America

²Department of Bioengineering, Samueli School of Engineering, University of California Los Angeles, Los Angeles, United States of America

³Division of Cardiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, United States of America

Presenting Author: Shu-Fu Shih

Synopsis

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References

1. Aletras AH, Ding S, Balaban RS, Wen H. DENSE: Displacement encoding with stimulated echoes in cardiac functional MRI. J Magn Reson 1999;137:247-252.

2. Kim D, Gilson WD, Kramer CM, Epstein FH. Myocardial tissue tracking with two-dimensional cine displacement-encoded MR imaging: Development and initial evaluation. Radiology 2004;230:862-871.

3. Zhong X, Spottiswoode BS, Meyer CH, Kramer CM, Epstein FH. Imaging three-dimensional myocardial mechanics using navigator-gated volumetric spiral cine DENSE MRI. Magn Reson Med 2010;64:1089-1097.

4. Spottiswoode BS, Zhong X, Hess AT, Kramer CM, Meintjes EM, Mayosi BM, et al. Tracking myocardial motion from cine DENSE images using spatiotemporal phase unwrapping and temporal fitting. IEEE Trans Med Imaging 2007;26:15-30.

5. Nwotchouang BST, Eppelheimer MS, Biswas D, Pahlavian SH, Zhong X, Oshinski JN, Barrow DL, Amini R, Loth F. Accuracy of cardiac-induced brain motion measurement using displacement-encoding with stimulated echoes (DENSE) magnetic resonance imaging (MRI): A phantom study. Magn Reson Med 2021;85:1237-1247.

6. Lin K, Meng L, Collins JD, Chowdhary V, Markl M, Carr JC. Reproducibility of cine displacement encoding with stimulated echoes (DENSE) in human subjects. Magn Reson Imaging 2017;35:148-153.

7. Auger DA, Ghadimi S, Cai X, Reagan CE, Sun C, Abdi M, et al. Reproducibility of global and segmental myocardial strain using cine DENSE at 3 T: a multicenter cardiovascular magnetic resonance study in healthy subjects and patients with heart disease. J Cardiovasc Magn Reson 2022;24:23.

8. Barbaroux, H., et al., DENSE-SIM: A modular pipeline for the evaluation of cine displacement encoding with stimulated echoes images with sub-voxel ground-truth strain. J Cardiovasc Magn Reson, 2025. 27(1): p. 101866.

9. Dorjsembe, Z., et al., Conditional Diffusion Models for Semantic 3D Brain MRI Synthesis. IEEE Journal of Biomedical and Health Informatics, 2024. 28(7): p. 4084-4093.

10. 1Abdi, M., et al., Suppression of artifact-generating echoes in cine DENSE using deep learning. Magnetic Resonance in Medicine, 2021. 86(4): p. 2095-2104.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/552-02-017