Hasegawa Hideyuki, Nagaoka Ryo
Faculty of Engineering, Academic Assembly, University of Toyama, 3190 Gofuku, Toyama, 930-8555, Japan.
Graduate School of Science and Engineering for Research, University of Toyama, 3190 Gofuku, Toyama, 930-8555, Japan.
J Med Ultrason (2001). 2020 Apr;47(2):203-210. doi: 10.1007/s10396-020-01009-7. Epub 2020 Feb 20.
The delay-and-sum beamformer is widely used in clinical ultrasound systems to obtain ultrasonic images. To improve image quality, the minimum variance (MV) beamformer was introduced in medical ultrasound imaging. The MV beamformer determines beamformer weights from ultrasonic echo signals received by individual transducer elements in an ultrasonic probe. In the present study, the MV beamformer was investigated to improve its performance.
In MV beamforming, a covariance matrix of echo signals received by individual elements needs to be estimated to obtain adaptive beamformer weights. To obtain a stable estimate, a total receiving aperture is divided into subarrays, and a covariance matrix is obtained using echo signals from each subarray to average covariance matrices from all subarrays. This procedure is called "subarray averaging." In the present study, a new method for estimation of the covariance matrix was proposed. In the proposed method, a covariance matrix, namely, a cross covariance matrix, is obtained using echo signals from different subarrays. Multiple covariance matrices are obtained from all different pairs of subarrays and averaged.
In the present study, the performance of the proposed method was evaluated by basic experiments on a phantom. Lateral spatial resolutions obtained by MV beamforming with conventional subarray averaging and the proposed method were similar. However, contrast obtained by MV beamforming with the proposed method was - 0.56 dB, which was significantly better than the - 5.06 dB obtained by MV beamforming with conventional subarray averaging.
Image contrast in MV beamforming could be improved significantly by estimating "cross" covariance matrices.
延迟求和波束形成器广泛应用于临床超声系统以获取超声图像。为提高图像质量，医学超声成像中引入了最小方差（MV）波束形成器。MV波束形成器根据超声探头中各个换能器元件接收到的超声回波信号确定波束形成器权重。在本研究中，对MV波束形成器进行了研究以提高其性能。
在MV波束形成中，需要估计各个元件接收到的回波信号的协方差矩阵以获得自适应波束形成器权重。为获得稳定估计，将总接收孔径划分为子阵列，并使用来自每个子阵列的回波信号获得协方差矩阵，以对所有子阵列的协方差矩阵进行平均。此过程称为“子阵列平均”。在本研究中，提出了一种估计协方差矩阵的新方法。在所提出的方法中，使用来自不同子阵列的回波信号获得协方差矩阵，即交叉协方差矩阵。从所有不同对子阵列中获得多个协方差矩阵并进行平均。
在本研究中，通过对体模进行基础实验评估了所提出方法的性能。使用传统子阵列平均和所提出方法的MV波束形成获得的横向空间分辨率相似。然而，使用所提出方法的MV波束形成获得的对比度为-0.56dB，明显优于使用传统子阵列平均的MV波束形成获得的-5.06dB。
通过估计“交叉”协方差矩阵可显著提高MV波束形成中的图像对比度。
