Robust broadband self-adaptive beamforming method used for ultrasound imaging

Abstract

The invention relates to a robust broadband self-adaptive beamforming method used for ultrasound imaging. The method comprises the steps that acquired ultrasonic echo data are converted from time domain to frequency domain, and band dividing is carried out; the covariance matrix of each subband divided from the band is calculated; according to the acquired covariance matrix, a feature space decomposition method is used to project an assumed steering vector into a signal subspace; a convex optimization method is used to estimate a true steering vector; the basic principle of a minimum variance method is used to acquire the beamforming processing result of each subband space; and the beamforming processing results of subband spaces are superimposed and are converted to time domain to acquire a final imaging output result. According to the invention, the broadband characteristic of an ultrasonic echo signal is fully used; the steering vector in real environment is reconstructed in frequency domain, so that the steering vector can have a robust performance in the case of phase distortion; and the ultrasound imaging quality can be improved under a non-homogeneous media.

Description

technical field [0001] The invention relates to the fields of medical ultrasonic diagnosis, ultrasonic non-destructive testing and the like, and in particular to a robust broadband adaptive beamforming method applied to ultrasonic imaging. Background technique [0002] The traditional medical ultrasonic diagnosis and ultrasonic non-destructive testing systems generally use the beamforming method of delay and superposition. This method is simple, reliable and easy to implement, but its performance is relatively general. In order to improve the quality of ultrasound imaging, the minimum variance adaptive beamforming method has received extensive attention, but this method faces the following two main problems: (1) The classic minimum variance beamforming method is proposed based on the narrowband signal model However, echo signals in the field of ultrasonic imaging generally belong to the category of broadband signals, so directly applying the minimum variance beamforming meth...

AI Technical Summary

Problems solved by technology

In order to improve the quality of ultrasound imaging, the minimum variance adaptive beamforming method has received extensive attention, but this method faces the following two main problems: (1) The classic minimum variance beamforming method is proposed based on the narrowband signal model However, echo signals in the field of ultrasonic imaging generally belong to the category of broadband signals, so directly applying the minimum variance beamforming method to ultrasonic imaging does not fully demonstrate the advantages of the original method; (2) For imaging of inhomogeneous media There are often phase distortions in the process, which leads to certain errors in the estimation of the covariance matrix and steering vector in the minimum variance beamforming method, which in turn affects the robustness of the method, making it difficult to achieve ideal performance in more complex application environments

However, the above methods are all focused on processing in the time domain, and have not fully considered the broadband characteristics of ultrasonic echo signals, nor have they been able to effectively estimate the mismatched steering vector under the condition of phase distortion, resulting in limited performance improvement.

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