22 February 2018 Eigenspace-based minimum variance adaptive beamformer combined with delay multiply and sum: experimental study
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Abstract
Delay and sum (DAS) is the most common beamforming algorithm in linear-array photoacoustic imaging (PAI) as a result of its simple implementation. However, it leads to a low resolution and high sidelobes. Delay multiply and sum (DMAS) was used to address the incapabilities of DAS, providing a higher image quality. However, the resolution improvement is not well enough compared to eigenspace-based minimum variance (EIBMV). In this paper, the EIBMV beamformer has been combined with DMAS algebra, called EIBMV-DMAS, using the expansion of DMAS algorithm. The proposed method is used as the reconstruction algorithm in linear-array PAI. EIBMV-DMAS is experimentally evaluated where the quantitative and qualitative results show that it outperforms DAS, DMAS and EIBMV. The proposed method degrades the sidelobes for about 365 %, 221 % and 40 %, compared to DAS, DMAS and EIBMV, respectively. Moreover, EIBMV-DMAS improves the SNR about 158 %, 63 % and 20 %, respectively.
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Moein Mozaffarzadeh, Moein Mozaffarzadeh, Ali Mahloojifar, Ali Mahloojifar, Mohammadreza Nasiriavanaki, Mohammadreza Nasiriavanaki, Mahdi Orooji, Mahdi Orooji, } "Eigenspace-based minimum variance adaptive beamformer combined with delay multiply and sum: experimental study", Proc. SPIE 10467, Photonics in Dermatology and Plastic Surgery 2018, 1046717 (22 February 2018); doi: 10.1117/12.2291533; https://doi.org/10.1117/12.2291533
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