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Article type: Research Article
Authors: Wang, Ping* | Shen, Yue | Chen, Jinghan | Li, Qianwen | Tong, Lin | Li, Xitao
Affiliations: State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing, China
Correspondence: [*] Corresponding author: Ping Wang, State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing, China. E-mail: [email protected].
Abstract: BACKGROUND: Beamforming is vital for medical ultrasound imaging systems. The generalized sidelobe canceller (GSC) beamforming can improve the image quality of lateral resolution, but its performance improvement in contrast and robustness is limited. OBJECTIVE: This paper proposes an improved generalized sidelobe canceller algorithm based on multi-apodization with cross-correlation (MAXB-IGSC), which aims to improve the contrast and robustness of ultrasound imaging while maintaining the high image resolution and background speckle quality of GSC. METHODS: The proposed MAXB-IGSC uses multiple pairs of complementary received apodization functions to process the echo data individually to obtain multiple pairs of data sets. The average of their normalized cross-correlation coefficients is then calculated and utilized to determine the adaptive subarray length of the GSC covariance matrix and weights the output of the improved GSC. RESULTS: The MAXB-IGSC improves the contrast ratio (CR) by 171.18% in anechoic cyst simulation and by 91.23%/130.97%/171.76% in geabr_0 (a dataset from the University of Michigan) experiment compared with GSC, respectively. Furthermore, MAXB-IGSC exhibits significant noise immunity, which greatly improves the robustness of the imaging. The technology also maintains the brightness and uniformity of the background speckle. CONCLUSION: The proposed MAXB-IGSC has potential for obtaining high-quality ultrasound images in clinical applications.
Keywords: Ultrasound imaging, cross-correlation coefficient, adaptive subarray length, robustness
DOI: 10.3233/THC-230724
Journal: Technology and Health Care, vol. 32, no. 3, pp. 1713-1731, 2024
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