Eigenspace-based Minimum Variance Beamforming Combined with General Coherence Factor for Ultrasound Beamforming
MENG Deming
CHEN Xin
DAI Ming
CHEN Siping
Abstract：To improve the quality of medical ultrasound imaging,a beamforming method which combines eigenspace-based mini-mum variance (ESBMV)with general coherence factor(GCF)was proposed.Firstly,minimum variance beamforming was used to obtain covariance matrix and weight vector;then the weight vector of the ESBMV was found by projecting the MV weight vector onto a vector subspace constructed from the eigenstructure of the covariance matrix;at the same time ,the data was transformed from array space to beamspace to calculate the general factor;in the end ,the general factor was used to optimize the results of eigenspace-based mini-mum variance beamforming.Simulations of point scatters and cyst phantom were 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.
Keywords：Medical ultrasound imagingAdaptive beamformingMinimum varianceEigenspaceGeneral coherence factor
Publication Date：2016-01-01
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：5( 219-223 )