iMAP Beamforming for High-Quality High Frame Rate Imaging

We present a statistical interpretation of beamforming to overcome the limitations of standard delay-and-sum (DAS) processing. Both the interference and the signal of interest are viewed as random variables, and the distribution of the signal of interest is exploited to maximize the a posteriori distribution of the aperture signals. In this formulation, the beamformer output is a maximum a posteriori (MAP) estimator of the signal of interest. We provide a closed-form expression for the MAP beamformer and estimate the unknown distribution parameters from the available aperture data using an empirical Bayes approach. We propose a simple scheme that iterates between the estimation of distribution parameters and the computation of the MAP estimator of the signal of interest, leading to an iterative MAP (iMAP) beamformer. This results in a suppression of the interference compared with DAS, without a severe increase in computational complexity or the need for fine-tuning of parameters. The effect of the proposed method on contrast is studied in detail and measured in terms of contrast ratio (CR), contrast-to-noise ratio (CNR), and contrast-to-speckle ratio (CSR). By implementing iMAP on both simulated and experimental data, we show that only 13 transmissions are required to obtain a CNR comparable to DAS with 75 plane waves. Compared to other interference suppression methods, such as coherence factor and scaled Wiener processing, iMAP shows an improved contrast and a better preserved speckle pattern.