Photoacoustic Imaging using Combination of Eigenspace-Based Minimum Variance and Delay-Multiply-and-Sum Beamformers: Simulation Study

摘要

Delay and Sum (DAS), as the most common beamforming algorithm inPhotoacoustic Imaging (PAI), having a simple implementation, results in alow-quality image. Delay Multiply and Sum (DMAS) was introduced to improve thequality of the reconstructed images using DAS. However, the resolutionimprovement is now well enough compared to high resolution adaptivereconstruction methods such as Eigenspace- Based Minimum Variance (EIBMV). Weproposed to integrate the EIBMV inside the DMAS formula by replacing theexisting DAS algebra inside the expansion of DMAS, called EIBMV-DMAS. It isshown that EIBMV-DMAS outperforms DMAS in the terms of levels of sidelobes andwidth of mainlobe significantly. For instance, at the depth of 35 mm,EIBMV-DMAS outperforms DMAS and EIBMV in the term of sidelobes for about 108dB, 98 dB and 44 dB compared to DAS, DMAS, and EIBMV, respectively. Thequantitative comparison has been conducted using Full-Width-Half-Maximum (FWHM)and Signal-to-Noise Ratio (SNR), and it was shown that EIBMV-DMAS reduces theFWHM about 1.65 mm and improves the SNR about 15 dB, compared to DMAS.