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Abstract #2735

4D Flow Imaging Incorporating a Fluid Dynamics Model

Anthony G. Christodoulou 1 , Rebecca Ramb 2 , Marius Menza 2 , Jrgen Hennig 2 , and Zhi-Pei Liang 1

1 Beckman Institute and Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 2 Department of Radiology, Medical Physics, University Medical Center, Freiburg, Baden-Wrttemburg, Germany

This work presents a method to accelerate 4D flow imaging using a physics-based image model. This model is generated by integrating computational fluid dynamics into image reconstruction: we solve the Navier-Stokes equations with boundary conditions reconstructed from limited (k,t)-space data, and we reconstruct 4D velocity-encoded images using the Navier-Stokes solution as a constraint. This physics-based constraint complements existing image models that enforce mathematical properties of cardiovascular images (e.g., sparsity, low-rankness) to further enhance the speed and reconstruction quality of 4D flow MRI.

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