Generalized sidelobe cancellation ultrasonic imaging method based on mixed subspace projection

Abstract

The invention relates to a generalized sidelobe cancellation ultrasonic imaging method based on mixed subspace projection, and belongs to the technical field of ultrasonic imaging. The method comprises the following steps: preprocessing a received echo signal; dividing sub-matrixes, and carrying out forward and backward smoothing and diagonal loading processing to obtain a sample covariance matrix; carrying out characteristic decomposition on the sample covariance matrix, and constructing a mixed signal subspace according to the characteristic value of the sample covariance matrix and the characteristic vector correlation between an expected direction vector and the sample covariance matrix; projecting the expected direction vector of a generalized sidelobe canceller to a left singular space of the mixed signal subspace, and constructing a new blocking matrix based on the improved expected direction vector; forming a generalized sidelobe cancellation beam; projecting the weight of thewave beam to the mixed signal subspace for correction; and carrying out weighted sum of an echo signal by using the corrected weight. According to the method, the robustness and the imaging quality ofa beam forming algorithm can be remarkably improved.

Description

technical field [0001] The invention belongs to the technical field of ultrasonic imaging, and relates to a generalized sidelobe cancellation ultrasonic imaging algorithm based on mixed subspace projection. Background technique [0002] Ultrasound imaging has the advantages of safety, real-time, convenience, etc., so it is widely used in the medical field. Digital beamforming is the most critical part of ultrasound imaging. The most widely used and simplest beamforming algorithm in the digital beamforming algorithm is the Delay And Sum (DAS) algorithm, which delays the received echo signal according to the geometric position relationship of the array element channel. Calculate, and then align and superimpose the delayed data. The traditional DAS algorithm has low complexity and fast imaging speed, but the width of the main lobe is increased and the resolution is low due to the weighting of the fixed window function. [0003] The minimum variance undistorted beamformer (Mi...

AI Technical Summary

Problems solved by technology

However, the generalized sidelobe cancellation algorithm based on feature space often causes image distortion in complex environment imaging.

Especially when imaging the background around strong speckles and strong scattering points, the algorithm will produce more serious black area artifacts

This is because the eigenvalues ​​corresponding to the interference and noise are larger than the eigenvalues ​​corresponding to the desired signal, which leads to the deterioration of the robustness of the traditional eigenspace generalized sidelobe canceller

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