Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/90871
Title: Sparsity-based beamforming to enhance two-dimensional linear-array photoacoustic tomography
Authors: Mozaffarzadeh, Moein
Periyasamy, Vijitha
Paridar, Roya
Pramanik, Manojit
Mehrmohammadi, Mohammad
Orooji, Mahdi
Keywords: Photoacoustic Imaging
Beamforming
DRNTU::Engineering::Chemical engineering
Issue Date: 2019
Source: Paridar, R., Mozaffarzadeh, M., Periyasamy, V., Pramanik, M., Mehrmohammadi, M., & Orooji, M. (2019). Sparsity-based beamforming to enhance two-dimensional linear-array photoacoustic tomography. Ultrasonics, 9655-63. doi:10.1016/j.ultras.2019.03.010
Series/Report no.: Ultrasonics
Abstract: In linear-array photoacoustic imaging (PAI), beamforming methods can be used to reconstruct the images. Delay-and-sum (DAS) beamformer is extensively used due to its simple implementation. However, this algorithm results in high level of sidelobes and low resolution. In this paper, it is proposed to form the photoacoustic (PA) images through a regularized inverse problem to address these limitations and improve the image quality. We define a forward/backward problem of the beamforming and solve the inverse problem using a sparse constraint added to the model which forces the sparsity of the output beamformed data. It is shown that the proposed Sparse beamforming (SB) method is robust against noise due to the sparsity nature of the problem. Numerical results show that the SB method improves the signal-to-noise ratio (SNR) for about 98.69 dB, 82.26 dB and 74.73 dB, in average, compared to DAS, delay-multiply-and-sum (DMAS) and double stage-DMAS (DS-DMAS), respectively. Also, quantitative evaluation of the experimental results shows a significant noise reduction using SB algorithm. In particular, the contrast ratio of the wire phantom at the depth of 30 mm is improved about 103.97 dB, 82.16 dB and 65.77 dB compared to DAS, DMAS and DS-DMAS algorithms, respectively, indicating a better performance of the proposed SB in terms of noise reduction.
URI: https://hdl.handle.net/10356/90871
http://hdl.handle.net/10220/48843
ISSN: 0041-624X
DOI: 10.1016/j.ultras.2019.03.010
Rights: © 2019 Elsevier. All rights reserved. This paper was published in Ultrasonics and is made available with permission of Elsevier.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCBE Journal Articles

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