Various methods are used in ultrasound beamforming to increase signal-to-noise ratio (SNR) and improve spatial resolution. SNR is typically improved by exploiting coherence in the RF channel data, for example summing channel data after applying focal delays in the delay-and-sum (DAS) beamformer, and summing channel data after applying a per-channel matched filter for the spatial matched filter beamformer[1]. Inverse filter methods are capable of improving spatial resolution at the cost of SNR [2],[3], or can trade resolution for SNR using a regularization parameter, but in general are very computationally intensive due to the large RF data sets used. We propose a post-processing method operating on post-summed but pre-envelope detected beamformed image data that can improve the pixel SNR and spatial resolution of any beamformer with low computational cost. This is achieved by forming a new pixel for each point in the image as a linear combination of the surrounding beamformed pixels. The weights for each pixel are calculated in advance using a quadratically constrained least squares method to reduce PSF energy outside the mainlobe and noise energy. Simulations indicate that this method can increase cystic contrast by up to 20dB without any cost in SNR, and can increase pixel SNR can by up 16dB without affecting contrast. Alternatively, simultaneous gains in contrast and SNR can be achieved. Experimental results show smaller performance improvements yet validate the feasibility of this technique.
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