Adaptive sidelobe reduction applied to ultrasound imaging

Minimum variance beamforming has been recently attended in medical ultrasound imaging. In spite of its capabilities in suppressing interferences resulting in an enhanced resolution, its computational complexity is a serious restriction for its implementing. In this paper, we study the outcomes of applying a class of parametric windows, in which the parameters are adaptively determined. Furthermore, we develop a new parametric window with improved resolution. The method employs a single realization full array data to estimate the interfering signals, based on which, the parameters of a parametric window are calculated in a way to minimize the squared value of the output. The structure of the window along with the additional L₂ norm constraint, guarantee the desired signal i.e. the signal received from on-axis, is passed without degradation, while minimizing the interferences. The most important advantage of the method presented here is the complexity proportional to the number of array elements, which is like a delay and sum beamformer, as well as outperforming it in resolution and contrast. The method also indicates better contrast than minimum variance beamformer.