Inspired by the F-DMAS beamforming in B-mode imaging, this work attempts to address the spatiotemporal sensitivity of the conventional flow imaging techniques with a novel non-linear beamforming approach without the use of any contrast agents and deep learning based methods. The major contributions of this work are as follows.
- A novel nonlinear beamforming technique is proposed for ultrasound flow imaging and the first effort towards the application of nonlinear beamforming in flow imaging.
- We validate the proposed nonlinear beamformer using typical parabolic flow simulations with a cross-correlation based velocity estimator and an autocorrelation based velocity estimator which are the common velocity estimation techniques in the literature.
- Further, the proposed approach has been thoroughly investigated for velocity sensitivity with in-vitro datasets including a rotating disk, air bubble tracking, and flow direction reversal. Finally, we report the in-vivo performance evaluation of the proposed approach for a typical pulsatile flow in a carotid artery dataset.
- The results, when compared to the state-of-the-art DAS based flow imaging approaches, suggest that the proposed method provides better spatiotemporal sensitivity towards the flow transients.
