A decimated minimum variance beamformer applied to ultrasound imaging

• The paper describes a new adaptive beamforming method with linear complexity.
• A decimated aperture data is used to apply the minimum variance beamforming.
• In complexity aspect, it is similar to the DAS, while outperforming in resolution.
• Compared to MV, it behaves more robust at the presence of errors.

Minimum variance beamforming has performed significant improvement in the resolution of the ultrasound images. However, its computational complexity is a serious problem. This paper introduces a new implementation of the minimum variance beamformer for ultrasound imaging with a focused transmit beam. In this method, a decimated aperture data instead of full of it, is used as the beamformer input, on which the minimum variance beamforming is applied, with the covariance matrix estimated using the full aperture data. In this way, the method can give a linear complexity while it can show a performance comparable to that of the full array implementation of the minimum variance beamforming, as the simulation and experimental results confirm this. Therefore, this adaptive beamforming method can be viewed as an approximate implementation of the minimum variance beamforming with a linear computational complexity.