Eigenspace-based minimum variance beamformer combined with sign coherence factor: Application to linear-array photoacoustic imaging

Sadaf Shamekhi; Vijitha Periyasamy; Manojit Pramanik; Mohammad Mehrmohammadi; Babak Mohammadzadeh Asl

doi:10.1016/j.ultras.2020.106174

Eigenspace-based minimum variance beamformer combined with sign coherence factor: Application to linear-array photoacoustic imaging

Ultrasonics. 2020 Dec:108:106174. doi: 10.1016/j.ultras.2020.106174. Epub 2020 May 22.

Authors

Sadaf Shamekhi¹, Vijitha Periyasamy², Manojit Pramanik², Mohammad Mehrmohammadi³, Babak Mohammadzadeh Asl⁴

Affiliations

¹ Department of Biomedical Engineering, Tarbiat Modares University, Tehran, Iran.
² School of Chemical and Biomedical Engineering, Nanyang Technological University, Singapore.
³ Department of Biomedical Engineering, Wayne State University, Detroit, MI, USA.
⁴ Department of Biomedical Engineering, Tarbiat Modares University, Tehran, Iran. Electronic address: babakmasl@modares.ac.ir.

PMID: 32502893
DOI: 10.1016/j.ultras.2020.106174

Abstract

Photoacoustic (PA) imaging combining the advantages of high resolution of ultrasound imaging and high contrast of optical imaging provides images with good quality. PA imaging often suffers from disadvantages such as clutter noises and decreased signal-to-noise-ratio at higher depths. One studied method to reduce clutter noises is to use weighting factors such as coherence factor (CF) and its modified versions that improve resolution and contrast of images. In this study, we combined the Eigen-space based minimum variance (EIBMV) beamformer with the sign coherence factor (SCF) and show the ability of these methods for noise reduction when they are used in combination with each other. In addition, we compared the proposed method with delay-and-sum (DAS) and minimum variance (MV) beamformers in simulated and experimental studies. The simulation results show that the proposed EIBMV-SCF method improves the SNR about 94 dB, 87.65 dB, and 62.29 dB compared to the DAS, MV, and EIBMV, respectively, and the corresponding improvements were 79.37/34.43 dB, 77.25/26.96 dB, and 33.19/25.56 dB in the ex vivo/in vivo experiments.

Keywords: Adaptive beamforming; Contrast enhancement; Image reconstruction; Noise reduction; Photoacoustic imaging.