3D Carotid Artery Flow Imaging Using Compressive Sensing with a Spatial Coding Mask
A Simulation Study
Yuyang Hu (Erasmus MC)
D. Doğan (TU Delft - Signal Processing Systems)
Michael Brown (Erasmus MC)
Mahé Bulot (Active Probe Group)
Guillaume Ferin (Active Probe Group)
GJT Leus (TU Delft - Signal Processing Systems)
P. Kruizinga (Erasmus MC)
A. F.W. Steen (Erasmus MC)
Johannes G. Bosch (Erasmus MC)
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Abstract
It has been previously demonstrated that applying an aberrating mask for 2D compressive imaging using a low number of sensors (elements) can significantly improve image resolution, as evaluated via the point spread function. Here we investigate the potential to apply a similar approach for 3D flow monitoring. We conducted a 3D k-Wave simulation using a 5x5 sensor array coupled to a physical coding mask, performing B-mode and power Doppler imaging on a 3D carotid artery flow model. An approximately three times smaller lateral PSF was achieved at the cost of increased background clutter level and slightly increased axial PSF. A better definition of the vessel border and finer flow speckle were observed in power Doppler imaging. Our results suggest that 3D compressive imaging using a very low sensor count of 25 with spatial coding mask has the potential to monitor 3D carotid artery flow.