关键词: 超声成像, 自适应波束形成, 最小方差, 特征空间, 空时相干系数

Abstract: To improve the quality of medical ultrasound imaging, a beamforming method which combines Eigen Space-Based Minimum Variance（ESBMV） with  Spatio-Temporally Coherence Factor（STCF） is proposed. Firstly, minimum variance beamforming is used to obtain covariance matrix and weight vector; then the weight vector of the ESBMV is found by projecting the  MV weight vector onto a vector subspace constructed from the eigenstructure of the covariance matrix; at the same time, the spatio-temporally method is used to calculate the coherence  factor; in the end, the spatio-temporally coherence factor is used to optimize the results of eigenspace-based minimum variance beamforming. Simulations of point scatters and cyst phantom are used to verify the proposed method. The results show that the proposed method provides improved contrast, better speckle performance and more robustness than the ESBMV and ESBMV-CF beamforming method, at the expense of slightly lower resolution.

Key words: ultrasound imaging, adaptive beamforming, minimum variance, eigenspace, Spatio-Temporally Coherence Factor（STCF）