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Delay and Sum (DAS) is the most prevalent beamformer in Photoacoustic Imaging (PAI), having a simple implementation, while it leads to a low-quality image. Delay-Multiply-and-Sum (DMAS) was proposed to improve, compared to DAS, the quality of the reconstructed images. However, the resolution improvement is not well enough compared to the high resolution adaptive reconstruction methods such as Eigenspace-Based Minimum Variance (EIBMV). We proposed to integrate the EIBMV inside the DMAS formula by replacing the existing DAS algebra inside the expansion of DMAS, called EIBMV-DMAS. It has been shown that EIBMV-DMAS significantly outperforms DMAS in the terms of level of sidelobes and width of mainlobe. For example, at the depth of 35 mm, EIBMV-DMAS outperforms DMAS and EIBMV in the term of sidelobes of about 108 dB, 98 dB and 44 dB compared to DAS, DMAS, and EIBMV, respectively. The quantitative comparison has been conducted using full-width-half-maximum (FWHM) and signal-to-noise ratio (SNR). It was demonstrated that EIBMV-DMAS reduces the FWHM about 1.65 mm and improves the SNR about 15 dB, compared to DMAS.

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