4.6 Article

Cross Subaperture Averaging Generalized Sidelobe Canceler Beamforming Applied to Medical Ultrasound Imaging

Journal

APPLIED SCIENCES-BASEL
Volume 11, Issue 18, Pages -

Publisher

MDPI
DOI: 10.3390/app11188689

Keywords

GSC-CROSS; adaptive beamforming; minimum variance; covariance matrix

Funding

  1. China National Key R&D Program during the 13th Five-year Plan Period [2018YFC0116202, 2017YFC0109702, 2017YFC0109901]

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The proposed GSC-CROSS approach for medical ultrasound imaging, using the cross-covariance matrix instead of the traditional covariance matrix estimation, significantly improves lateral resolution and contrast. Experimental results demonstrate the method's superiority in imaging of scattering points and cyst targets.
For adaptive ultrasound imaging, a reliable estimation of the covariance matrix has a decisive influence on the performance of beamformers. In this paper, we propose a new cross subaperture averaging generalized sidelobe canceler approach (GSC-CROSS) for medical ultrasound imaging, which uses the cross-covariance matrix instead of the traditional covariance matrix estimation. By using the more stable and accurate estimation of the covariance matrix, GSC-CROSS performs well in both lateral resolution and contrast. Experiments are conducted based on the simulated echo data of scattering points and a cyst target. Beamforming responses of scattering points show that GSC-CROSS can improve the lateral resolution by 76.9%, 68.8%, and 17.1% compared with delay-and-sum (DS), synthetic aperture (SA), and the traditional generalized sidelobe canceler (GSC), respectively. Also, imaging of the cyst target shows that compared with DS, SA, and GSC, the contrast increases by 101%, 32.6%, and 63.5%, respectively. Finally, the actual echo data collected from a medical ultrasonic imaging system is applied to reconstruct the image. Results show that the proposed method has a good performance on lateral resolution and contrast. Both the simulated and experimental data demonstrate the effectiveness of the proposed method.

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