iMAP Beamforming for High Quality High Frame Rate Imaging
Tanya Chernyakova, Dan Cohen, Meged Shoham, Yonina C. Eldar

TL;DR
This paper introduces an iterative MAP beamforming method (iMAP) that significantly enhances image contrast in high frame rate ultrasound imaging by statistically modeling signals, outperforming traditional methods with minimal additional computational cost.
Contribution
The paper presents a novel iterative MAP beamformer that exploits statistical signal modeling, improving contrast and speckle preservation in ultrasound imaging with fewer transmissions.
Findings
iMAP achieves contrast comparable to traditional methods with fewer transmissions.
The method outperforms coherence factor and Wiener processing in contrast enhancement.
iMAP maintains speckle pattern integrity better than existing interference suppression techniques.
Abstract
We present a statistical interpretation of beamforming to overcome 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 estimation of distribution parameters and computation of the MAP estimator of the signal of interest, leading to an iterative MAP (iMAP) beamformer. This results in a significant improvement of the contrast compared to DAS without…
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