改进的低复杂度幅度相位估计波束形成算法
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摘要
针对低复杂度的最小方差方法虽降低计算复杂度但成像质量不高的问题,提出了一种改进的低复杂度幅度相位估计波束形成算法.通过抽取协方差矩阵的有效行来计算自适应加权值,其中,有效行数的选取由更加准确的高斯相位相干系数确定,然后再用高斯相位相干因子对加权矢量做进一步修正,从而达到降低复杂度的同时保证成像质量的目的.通过实验验证,将改进算法与原算法和另一种降低复杂度的波束域方法进行对比分析,充分证明了改进算法在降低复杂度和提升成像质量方面的优越性.
To improve the imaging quality in the minimum variance method of low complexity,an improved low-complexity amplitude and phase estimation beamforming algorithm w as proposed. The adaptive w eighted value w as calculated by extracting the effective row s of the covariance matrix,w here the selection of the effective number of row s w as determined by a more accurate Gaussian phase coherence coefficient,w hich w as then used to modify the w eighting vector in order to reduce the complexity and ensure the quality of the imaging at the same time.Through experimental verification, the improved algorithm w as compared w ith the original algorithm and another beamspace method to reduce the complexity, which fully proves the superiority of the improved algorithm in reducing the complexity and improving the imaging quality.
To improve the imaging quality in the minimum variance method of low complexity,an improved low-complexity amplitude and phase estimation beamforming algorithm w as proposed. The adaptive w eighted value w as calculated by extracting the effective row s of the covariance matrix,w here the selection of the effective number of row s w as determined by a more accurate Gaussian phase coherence coefficient,w hich w as then used to modify the w eighting vector in order to reduce the complexity and ensure the quality of the imaging at the same time.Through experimental verification, the improved algorithm w as compared w ith the original algorithm and another beamspace method to reduce the complexity, which fully proves the superiority of the improved algorithm in reducing the complexity and improving the imaging quality.
引文
[1] Synnevag J F,Austeng A,Holm S. Adaptive beamforming applied to medical ultrasound imaging[J]. IEEE Transactions on Ultrasonics,Ferroelectrics and Frequency Control,2007,54(8):1603-1613.
[2] Mehdizadeh S,Austeng A,Johansen T F,et al. Eigenspace based minimum variance beamforming applied to ultrasound imaging of acoustically hard tissues[J]. IEEE Transactions on Medical Imaging,2012,31(10):1912-1921.
[3] Zeng X,Chen C, Wang Y. Eigenspace-based minimum variance beamformer combined with Wiener postfilter for medical ultrasound imaging[J]. Ultrasonics,2012,52(8):996-1004.
[4] Wang S L,Li P C. MVDR-based coherence weighting for highframe-rate adaptive imaging[J]. IEEE Transactions on Ultrasonics,Ferroelectrics and Frequency Control,2009,56(10):2097-2110.
[5] Nilsen C I C,Hafizovic I. Beamspace adaptive beamforming for ultrasound imaging[J]. IEEE Transactions on Ultrasonics,Ferroelectrics and Frequency Control,2009,56(10):2187-2197.
[6] Vignon F,Burcher M R. Capon beamforming in medical ultrasound imaging with focused beams[J]. IEEE Transactions on Ultrasonics,Ferroelectrics and Frequency Control,2008,55(3):619-628.
[7] Synnevag J F,Holm S,Austeng A. A low complexity datadependent beamformer[J]. Ultrasonics Symposium,2008,58:1084-1087.
[8] Asl B M, Mahloojifar A. A low-complexity adaptive beamformer for ultrasound imaging using structured covariance matrx[J]. IEEE Transactions on Ultrasonics,Ferroelectrics and Frequency Control,2012,59(4):660-667.
[9] Deylami A M,Asl B M. Low complex subspace minimum variance beamformer for medical ultrasound imaging[J].Ultrasonics,2016,66:43-53.
[10]佘黎煌,闫鑫,张石.结合子空间投影的幅度相位估计波束形成算法[J].东北大学学报(自然科学版),2018,39(7):927-930.(She Li-huang,Yan Xin,Zhang Shi. Amplitude and phase estimation beamforming algorithm combined with subspace projection[J]. Journal of Northeastern University(Natural Science),2018,39(7):927-930.)
[11] Hasegawa H. Enhancing effect of phase coherence factor for improvement of spatial resolution in ultrasonic imaging[J].Journal of Medical Ultrasonics,2016,43(1):1-9.
[2] Mehdizadeh S,Austeng A,Johansen T F,et al. Eigenspace based minimum variance beamforming applied to ultrasound imaging of acoustically hard tissues[J]. IEEE Transactions on Medical Imaging,2012,31(10):1912-1921.
[3] Zeng X,Chen C, Wang Y. Eigenspace-based minimum variance beamformer combined with Wiener postfilter for medical ultrasound imaging[J]. Ultrasonics,2012,52(8):996-1004.
[4] Wang S L,Li P C. MVDR-based coherence weighting for highframe-rate adaptive imaging[J]. IEEE Transactions on Ultrasonics,Ferroelectrics and Frequency Control,2009,56(10):2097-2110.
[5] Nilsen C I C,Hafizovic I. Beamspace adaptive beamforming for ultrasound imaging[J]. IEEE Transactions on Ultrasonics,Ferroelectrics and Frequency Control,2009,56(10):2187-2197.
[6] Vignon F,Burcher M R. Capon beamforming in medical ultrasound imaging with focused beams[J]. IEEE Transactions on Ultrasonics,Ferroelectrics and Frequency Control,2008,55(3):619-628.
[7] Synnevag J F,Holm S,Austeng A. A low complexity datadependent beamformer[J]. Ultrasonics Symposium,2008,58:1084-1087.
[8] Asl B M, Mahloojifar A. A low-complexity adaptive beamformer for ultrasound imaging using structured covariance matrx[J]. IEEE Transactions on Ultrasonics,Ferroelectrics and Frequency Control,2012,59(4):660-667.
[9] Deylami A M,Asl B M. Low complex subspace minimum variance beamformer for medical ultrasound imaging[J].Ultrasonics,2016,66:43-53.
[10]佘黎煌,闫鑫,张石.结合子空间投影的幅度相位估计波束形成算法[J].东北大学学报(自然科学版),2018,39(7):927-930.(She Li-huang,Yan Xin,Zhang Shi. Amplitude and phase estimation beamforming algorithm combined with subspace projection[J]. Journal of Northeastern University(Natural Science),2018,39(7):927-930.)
[11] Hasegawa H. Enhancing effect of phase coherence factor for improvement of spatial resolution in ultrasonic imaging[J].Journal of Medical Ultrasonics,2016,43(1):1-9.