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An advanced sparsity-based photoacoustic image reconstruction algorithm for linear-array transducer scenario
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Paper Abstract

One of the most common algorithms used in linear-array photoacoustic imaging, is Delay-and-Sum (DAS) beamformer due to its simple implementation. The results show that this algorithm results in a low resolution and high sidelobes. In this paper, it is proposed to use the sparse-based algorithm in order to suppress the noise level efficiently and improve the image quality. The forward problem of the beamforming is defined through a Least square (LS) method, and a ℓ1-norm regularization term is added to the problem which forces the sparsity of the output 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 results show that SB leads to signal-to-noise-ratio improvement about 98.69 dB and 82.26 dB, in average, compared to DAS and Delay-Multiply-and-Sum (DMAS), respectively. Also, the full-width-half-maximum is improved about 396 μm and 123 μm, in average, compared to DAS and DMAS algorithms, respectively, using the proposed SB method, which indicates the good performance of SB method in image enhancement.

Paper Details

Date Published: 27 February 2019
PDF: 7 pages
Proc. SPIE 10878, Photons Plus Ultrasound: Imaging and Sensing 2019, 108786O (27 February 2019); doi: 10.1117/12.2508039
Show Author Affiliations
Roya Paridar, Tarbiat Modares Univ. (Iran, Islamic Republic of)
Moein Mozaffarzadeh, Tarbiat Modares Univ. (Iran, Islamic Republic of)
Maryam Basij, Wayne State Univ. (United States)
Mohammad Mehrmohammadi, Wayne State Univ. (United States)
Mahdi Orooji, Tarbiat Modares Univ. (Iran, Islamic Republic of)


Published in SPIE Proceedings Vol. 10878:
Photons Plus Ultrasound: Imaging and Sensing 2019
Alexander A. Oraevsky; Lihong V. Wang, Editor(s)

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