Non-linear High Resolution (NLHR) Beamforming for Flow

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.

  1. A novel nonlinear beamforming technique is proposed for ultrasound flow imaging and the first effort towards the application of nonlinear beamforming in flow imaging.

  2. 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.

  3. 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.

  4. 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.


    Tracking of simulated pulsatile flows having five distinct impulses of different durations
    Tracking of simulated pulsatile flows having five impulses of different velocity changes
    Non-linear Beamforming for In Vivo Carotid
    Non-linear Beamforming for Air Bubble Tracking
    Non-linear beamforming results for flow Direction Reversal
    Non-linear beamforming for typical Pulsatile Flow
    Non-linear beamforming for a rotating disk