Improvement of performance of minimum variance beamformer by introducing cross covariance estimate

Purpose: 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. Methods: 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. Results: 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. Conclusion: Image contrast in MV beamforming could be improved significantly by estimating “cross” covariance matrices.