6 February 2018 Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming algorithm
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Abstract
In photoacoustic imaging, delay-and-sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely delay-multiply-and-sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a beamformer is introduced using minimum variance (MV) adaptive beamforming combined with DMAS, so-called minimum variance-based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation results in multiple terms representing a DAS algebra. It is proposed to use the MV adaptive beamformer instead of the existing DAS. MVB-DMAS is evaluated numerically and experimentally. In particular, at the depth of 45 mm MVB-DMAS results in about 31, 18, and 8 dB sidelobes reduction compared to DAS, MV, and DMAS, respectively. The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively. In particular, at the depth of 33 mm of the experimental images, MVB-DMAS results in about 20 dB sidelobes reduction in comparison with other beamformers.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Moein Mozaffarzadeh, Ali Mahloojifar, Mahdi Orooji, Karl Kratkiewicz, Saba Adabi, Mohammadreza Nasiriavanaki, "Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming algorithm," Journal of Biomedical Optics 23(2), 026002 (6 February 2018). https://doi.org/10.1117/1.JBO.23.2.026002 . Submission: Received: 18 October 2017; Accepted: 8 January 2018
Received: 18 October 2017; Accepted: 8 January 2018; Published: 6 February 2018
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