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Unified pixel-based (PB) beamforming has been implemented for ultrasound imaging, offering significant enhancements in lateral resolution compared to the conventional dynamic focusing. However, it still suffers from clutter and off-axis artifacts, limiting the contrast resolution. This paper proposes an efficient method to improve image quality by integrating filtered delay multiply and sum (F-DMAS) into the framework. This hybrid strategy incorporates the spatial coherence of the received data into the beamforming process to improve contrast resolution and clutter rejection in the generated image. We also integrate a Wiener filter to suppress the spatiotemporal spreading using signals echoed from a single scatterer at the transmit focus as a kernel for the deconvolution. The Wiener filter is applied to the received waveforms before performing the hybrid strategy. The Wiener filter is shown to reduce interference due to the interaction between the excitation pulse and the transfer functions of the transducer elements, thus benefiting the axial resolution of the generated images. We validate the proposed method and compare it with other beamforming strategies through a series of experiments, including simulation, phantom, and in vivo studies. The results show that our approach can substantially improve both spatial resolution and contrast over the unified PB algorithm, while still maintaining the good features of this beamformer. The simplicity and good performance of our method show its potential for use in clinical applications., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Pixel-based beamforming generates focused data by assuming that the waveforms received on a linear transducer array are composed of spherical pulses. It does not take into account the spatiotemporal spread in the data from the length of the excitation pulse or from the transfer functions of the transducer elements. As a result, these beamformers primarily have impacts on lateral, rather than axial, resolution. This paper proposes an efficient method to improve the axial resolution for pixel-based beamforming. We extend our field pattern analysis and show that the received waveforms should be passed through a Wiener filter before being used in the coherent pixel-based beamformer. This filter is designed based on signals echoed from a single scatterer at the transmit focus. The beamformer output is then combined with a coherence factor, that is adaptive to the signal-to-noise ratio, to improve the image contrast and suppress artifacts that have arisen during the filtering process. We validate the proposed method and compare it with other beamforming strategies using a series of experiments, including simulation, phantom and in vivo studies. It is shown to offer significant improvements in axial resolution and contrast over coherent pixel-based beamforming, as well as other spatial filters derived from synthetic aperture imaging. The method also demonstrates robustness to modeling errors in the experimental data. Overall, the imaging results show that the proposed approach has the potential to be of value in clinical applications., (Copyright © 2021 Elsevier B.V. All rights reserved.)