We present a 5D Flow MRI approach for mapping the Reynolds stress tensor in the in-vivo aorta within 6 minutes. First and second statistical moments of fluctuating velocities are encoded using six different velocity encoding gradient directions embedded in a Cartesian Golden angle undersampling scheme with data-driven motion detection and locally low-rank imaging reconstruction. It is demonstrated that this approach permits a time-efficient assessment of velocity vector fields, turbulent kinetic energy and Reynolds shear stresses of the aorta in-vivo.
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