An Angle Independent Depth Aware Fusion Beamforming Approach for Ultrafast Ultrasound Flow Imaging

TL;DR

This paper introduces a novel depth-aware fusion beamforming method for ultrafast ultrasound flow imaging that combines directional and triangulation techniques based on flow characteristics, improving accuracy and reducing bias.

Contribution

The paper presents an angle independent, depth aware fusion beamforming approach that adaptively combines flow estimation techniques based on flow nature, enhancing flow imaging accuracy.

Findings

67.62% reduction in magnitude bias compared to triangulation-based beamforming

74.71% reduction in magnitude bias compared to directional beamforming

Slight reduction in standard deviation of flow estimates

Abstract

In the case of vector flow imaging systems, the most employed flow estimation techniques are the directional beamforming based cross correlation and the triangulation-based autocorrelation. However, the directional beamforming-based techniques require an additional angle estimator and are not reliable if the flow angle is not constant throughout the region of interest. On the other hand, estimates with triangulation-based techniques are prone to large bias and variance at low imaging depths due to limited angle for left and right apertures. In view of this, a novel angle independent depth aware fusion beamforming approach is proposed and evaluated in this paper. The hypothesis behind the proposed approach is that the peripheral flows are transverse in nature, where directional beamforming can be employed without the need of an angle estimator and the deeper flows being non-transverse and directional, triangulation-based vector flow imaging can be employed. In the simulation study, an overall 67.62% and 74.71% reduction in magnitude bias along with a slight reduction in the standard deviation are observed with the proposed fusion beamforming approach when compared to triangulation-based beamforming and directional beamforming, respectively, when implemented individually. The efficacy of the proposed approach is demonstrated with in-vivo experiments.