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Pixel-based approach to delay multiply and sum beamforming in combination with Wiener filter for improving ultrasound image quality.

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Guo, Hao 
Xie, Hui-Wen 
Zhou, Guang-Quan 
Nguyen, Nghia Q 
Prager, Richard W 


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.



Delay multiply and sum, Image quality, Pixel-based, Ultrasound beamforming, Wiener-filter, Image Processing, Computer-Assisted, Ultrasonography, Phantoms, Imaging, Algorithms, Artifacts

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Elsevier BV
Cambridge University-Nanjing Centre of Technology and Innovation (Unknown)
The work was partially supported by the Cambridge Nanjing Centre for Technology and Innovation.