An Advanced Sparsity-based Photoacoustic Image Reconstruction Algorithm for Linear-Array Transducer Scenario

摘要

One of the most common algorithms used in linear-array photoacoustic imaging, is Delay-and-Sum (DAS) beam-former due to its simple implementation. The results show that this algorithm results in a low resolution andhigh sidelobes. In this paper, it is proposed to use the sparse-based algorithm in order to suppress the noise leveleu000eciently and improve the image quality. The forward problem of the beamforming is dened through a Leastsquare (LS) method, and a ℓ_1-norm regularization term is added to the problem which forces the sparsity of theoutput to the existing minimization problem. The new robust method, named sparse beamforming (SB) method,significantly suppresses the sidelobes and reduces the noise level due to the sparse added term. Numerical resultsshow that SB leads to signal-to-noise-ratio improvement about 98.69 dB and 82.26 dB, in average, compared toDAS and Delay-Multiply-and-Sum (DMAS), respectively. Also, the full-width-half-maximum is improved about396 μm and 123 μm, in average, compared to DAS and DMAS algorithms, respectively, using the proposed SBmethod, which indicates the good performance of SB method in image enhancement.