Abstract

A new adaptive weighting method [delay-and-sum-to-delay-standard-deviation factor (DASDSF)] combined with minimum variance (MV) beamforming is introduced in photoacoustic imaging (PAI). Existing MV-based beamformers improve photoacoustic image quality in terms of achieving narrow main lobes and, thus, improving spatial resolution. But, the beamformers give a strong side-lobe signal strength that greatly degrades the reconstructed image contrast. As a feedback weighting factor, DASDSF addresses the persisting side-lobe issue present in MV-beamformed images, i.e., our proposed method is robust against reduction in noises as well as side lobes, and it outperforms MV and MV combined with coherence factor beamformers. Validation studies—being carried out both in numerical simulation and experiments employing a low-cost (16 elements) linear transducer array in a home-built PAI system—demonstrate an excellent performance of the proposed weighting approach in improving SNR, while reducing main-lobe width (i.e., FWHM) and side-lobe signal strength. The study demonstrates that the proposed algorithm holds promise for development of a cost-effective PAI system using a low-cost linear transducer (${\sim}16$ elements against ${\sim}128$ generally used).

© 2021 Optical Society of America

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