452-03-010 / 452-03-010 ISMRM Abstract

On super-resolution in 4D flow MRI

Primary: Analysis Methods - Image Enhancement

Secondary: Cardiovascular - Flow

452-03-010 · Next-Generation MRI Image Enhancement · Tuesday, 12 May, 4:00 PM–5:36 PM · Power Pitch Theatre 2

Keywords: 4D flow MRI Super Resolution Physics-informed Neural Networks Artificial Intelligence (AI) Data Processing. hemodynamics. 4D flow MRI

Accepted

Luuk Jacobs ¹, Pietro Dirix¹, Simone Sgorbati^1,2, Stefano Buoso¹, Sebastian Kozerke¹

¹University and ETH Zürich, Zürich, Switzerland

²Politecnico di Milano, Milano, Italy

Presenting Author: Luuk Jacobs

Synopsis

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References

1. Markl, M., Frydrychowicz, A., Kozerke, S., Hope, M. & Wieben, O. 4D flow MRI. J. Magn. Reson. Imaging 36, 1015–1036 (2012).

2. Cibis, M. et al. The Effect of Spatial and Temporal Resolution of Cine Phase Contrast MRI on Wall Shear Stress and Oscillatory Shear Index Assessment. PLOS ONE 11, e0163316 (2016).

3. Shannon, C. E. A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423 (1948).

4. Jasak, H., Jemcov, A. & Tukovic, Z. OpenFOAM: A C++ Library for Complex Physics Simulations.

5. Dirix, P., Jacobs, L., Buoso, S. & Kozerke, S. Synthesizing Scalable CFD-Enhanced Aortic 4D Flow MRI for Assessing Accuracy and Precision of Deep-Learning Image Reconstruction and Segmentation Tasks. in Simulation and Synthesis in Medical Imaging (eds. Fernandez, V. et al.) 157–166 (Springer Nature Switzerland, Cham, 2025). doi:10.1007/978-3-031-73281-2_15. [doi]

6. Ferdian, E. et al. 4DFlowNet: Super-Resolution 4D Flow MRI Using Deep Learning and Computational Fluid Dynamics. Front. Phys. 8, (2020).

7. Raissi, M., Perdikaris, P. & Karniadakis, G. E. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. J. Comput. Phys. 378, 686–707 (2019).

8. Shone, F. et al. Deep Physics-Informed Super-Resolution of Cardiac 4D-Flow MRI. in Information Processing in Medical Imaging (eds. Frangi, A., de Bruijne, M., Wassermann, D. & Navab, N.) 511–522 (Springer Nature Switzerland, Cham, 2023). doi:10.1007/978-3-031-34048-2_39. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/452-03-010