Improving Ultrasound Imaging using Strong Reflectors Analysis and Processing

Background - An ultrasound (US) image is commonly formed using Delay-and-Sum (DAS) beamforming with fixed weighting. The main disadvantages of this beamforming technique are wide main-lobe and significant side-lobes. This leads to distorted US imaging since strong reflections that penetrate through the side-lobes obscure the imaging of weak reflectors received through the main-lobe. Apodization beamforming alone does not improve the US imaging angular resolution enough. Methods - We propose to detect strong reflectors of the imaging, and by deconvolution remove most of their distorting contribution from the US sampled data. We then build an image of weak reflectors using apodization beamforming. Lastly, the strong reflectors are artificially added back to the image based on their reflection through the main-lobe. To achieve this goal, we accordingly introduce an algorithm for locating and modelling strong reflectors with minimum assumptions or a-priori knowledge. Results - Based on 10,000 in-silico simulations, we show that the location and reflectivity of a sole randomly located strong reflector are extracted with good accuracy for reflectivity values of 13-33dB higher than its neighbourhood. It is demonstrated that after subtracting the distortion associated with the strong reflectors, including through the side-lobes, the reflectivity function of the weaker reflectors is faithfully recovered. We also qualitatively present the effect of the proposed method on both in-vivo and in-silico examples. Conclusion - Our results show that the proposed approach to ultrasound imaging can significantly improve image quality. Moreover, by removing the strong reflectors before beamforming, we can get a higher dynamic range image.