Adaptive beamforming with automatic diagonal loading in medical ultrasound imaging

Abstract

In medical ultrasound imaging, the most famous adaptive beamforming algorithm is the minimum variance (MV). Diagonal loading (DL) method is usually used to improve the robustness of the MV. Conventional DL methods have a critical problem which is determining the loading factor ignoring the input data. To address this problem, in this paper, using the shrinkage algorithm is proposed in which the loading coefficient is completely automated and determined by the input data. The performance of the proposed algorithm is evaluated by simulated ultrasound data in Field II. In point targets simulation, it has been shown that the proposed method improves the resolution about 87% and 20%, compared to delay and sum (DAS) and MV algorithms (with a fixed loading coefficient of), respectively. In addition, in anechoic cyst simulation, the contrast and relative contrast of the proposed method has been retained, in comparison to those of the MV beamformer, while they are improved about 5% and 18%, in comparison to the DAS ones, respectively.