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A Low-Complexity Beamformer for Ultrasound Imaging Based on Sub-Beamformer and Multi-Apodization With Cross-Correlation.

Authors :
Shen, Yue
Wang, Ping
Tong, Lin
Chen, Jinghan
Li, Qianwen
Zhu, Jinchan
Wang, Kunlin
Zeng, Jingya
Source :
Ultrasound in Medicine & Biology. Oct2024, Vol. 50 Issue 10, p1551-1565. 15p.
Publication Year :
2024

Abstract

This paper proposes an ultrasound imaging algorithm based on sub-beamformer and multi-apodization with cross-correlation (SUB-MAX), aiming to achieve high resolution close to the minimum variance (MV) beamforming with low complexity and to enhance image contrast while maintaining background quality. The output of two (N /2)-element DAS beamformers with asymmetric phase centers is subtracted, resulting in a large drop in the main-lobe amplitude, while the sidelobe maintains a relatively high amplitude level. Inspired by this characteristic, the coefficients with opposite trends compared with the subtracted output are obtained and fused with the normalized cross-correlation (NCC) weighting matrix acquired by using multi-pair received apodization, the proposed SUB-MAX obtains a new weighting matrix to weight the output of the DAS beamformer. For ats_wire point targets, the average full-width at half-maximum (FWHM) of SUB-MAX compared with DAS, DMAS, CF, and MAX decreases by 52.7%, 43.5%, 33.3%, and 52.7%, respectively. For geabr_0 cysts, the average contrast ratio (CR) of SUB-MAX compared with DAS, MV, DMAS, and CF increases by 57.7%, 86.8%, 2.5%, and 14.4%, respectively. Experiments on rat_tumor dataset also indicate that SUB-MAX has a superior comprehensive imaging performance. The experimental results indicate that the superior comprehensive imaging performance of the proposed SUB-MAX is expected to be suitable for real-time imaging systems due to its non-reliance on covariance matrix inversion. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03015629
Volume :
50
Issue :
10
Database :
Academic Search Index
Journal :
Ultrasound in Medicine & Biology
Publication Type :
Academic Journal
Accession number :
179396608
Full Text :
https://doi.org/10.1016/j.ultrasmedbio.2024.06.011