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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