Beam multiply and sum: A tradeoff between delay and sum and filtered delay multiply and sum beamforming for ultrafast ultrasound imaging

The delay and sum (DAS) has been the popular beamforming algorithm for image reconstruction in ultrafast ultrasound imaging systems due to its low complexity implementation. However, to improve the lower contrast and resolution in images reconstructed using DAS, there have been many adaptive and non-linear beamforming algorithms developed in the recent past. One of the popular non-linear algorithms proposed in the literature, filtered delay multiply and sum (F-DMAS) is sensitive to off-axis clutters and produces artifacts that result in the degradation of the overall image quality along with a possible dynamic range alteration. In this work, a novel approach to combining the strengths of DAS and F-DMAS algorithms is proposed. The proposed approach referred to as beam multiply and sum (BMAS), employs a DAS beamformer in multiple sub-apertures at receive to form the sub-aperture beams and cross multiplies them using a multiply and sum architecture to enhance the spatial coherence and suppress the clutter artifacts. An exhaustive performance comparison in terms of dynamic range alteration, resolution, and contrast of the BMAS is performed with standard in-silico and in-vitro datasets. The results suggest that the proposed approach outperforms the DAS and F-DMAS beamformers in most cases. More than the proposal of a novel beamforming algorithm, to the best of our knowledge, the approach is the first attempt of its kind towards the possibility of the co-existence of two or more beamformers in an ultrasound imaging system. With optimal tuning, it could provide a good trade-off between the effects of improved resolution and improved contrast while keeping the dynamic range linearity unaltered. •A novel approach to combine the strengths of DAS and F-DMAS algorithms is proposed.•Demonstrates the co-existence of two beamformers in ultrasound imaging.•Proposed beamformer is evaluated with exhaustive simulations and experimental dataset.•A trade-off between image quality and complexity of DAS and F-DMAS is achieved.