Row-column arrays have been shown to be able to generate 3-D ultrafast ultrasound images with an order of magnitude less independent electronic channels than traditional 2-D matrix arrays. Unfortunately, row-column array images suffer from major imaging artefacts due to high side-lobes, particularly when operating at high frame rates. This paper proposes a rowcolumn specific beamforming technique, for orthogonal plane wave transmissions, that exploits the incoherent nature of certain row-column array artefacts. A series of volumetric images are produced using row or column transmissions of 3-D plane waves. The voxel-wise geometric mean of the beamformed volumetric images from each row and column pair is taken prior to compounding, which drastically reduces the incoherent imaging artefacts in the resulting image compared to traditional coherent compounding. The effectiveness of this technique was demonstrated in silico and in vitro, and the results show a significant reduction in side-lobe level with over 16 dB improvement in sidelobe to main-lobe energy ratio. Significantly improved contrast was demonstrated with contrast ratio increased by ∼10dB and generalised contrast-to-noise ratio increased by 158% when using the proposed new method compared to existing delay and sum during in vitro studies. The new technique allowed for higher quality 3-D imaging whilst maintaining high frame rate potential.

Objective Super-resolution ultrasound (SRUS) imaging through localising and tracking sparse microbubbles has been shown to reveal microvascular structure and flow beyond the wave diffraction limit. Most SRUS studies use standard delay and sum (DAS) beamforming, where high side lobes and broad main lobes make isolation and localisation of densely distributed bubbles challenging, particularly in 3D due to the typically small aperture of matrix array probes. Method This study aimed to improve 3D SRUS by implementing a new fast 3D coherence beamformer based on channel signal variance. Two additional fast coherence beamformers, that have been implemented in 2D were implemented in 3D for the first time as comparison: a nonlinear beamformer with p -th root compression and a coherence factor beamformer. The 3D coherence beamformers, together with DAS, were compared in computer simulation, on a microflow phantom and in vivo . Results Simulation results demonstrated that all three adaptive weight-based beamformers can narrow the main lobe, suppress the side lobes, while maintaining the weaker scatter signals. Improved 3D SRUS images of microflow phantom and a rabbit kidney within a 3-second acquisition were obtained using the adaptive weight-based beamformers, when compared with DAS. Conclusion The adaptive weight-based 3D beamformers can improve the SRUS and the proposed variance-based beamformer performs best in simulations and experiments. Significance Fast 3D SRUS would significantly enhance the potential utility of this emerging imaging modality in a broad range of biomedical applications.

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