Medical Photoacoustic Beamforming Using Minimum Variance-Based Delay Multiply and Sum

TL;DR

This paper introduces a novel photoacoustic beamforming algorithm combining Minimum Variance adaptive beamforming with Delay-Multiply-and-Sum, significantly improving image resolution and SNR over traditional methods.

Contribution

The paper proposes the MVB-DMAS algorithm, integrating MV adaptive beamforming into DMAS, to enhance photoacoustic image quality beyond existing DAS, DMAS, and MV methods.

Findings

MVB-DMAS achieves about 13 dB higher SNR than DAS.

It provides better image resolution and sidelobe suppression.

The method outperforms existing beamformers in numerical evaluations.

Abstract

Delay-and-Sum (DAS) beamformer is the most common beamforming algorithm in Photoacoustic imaging (PAI) due to its simple implementation and real time imaging. However, it provides poor resolution and high levels of sidelobe. A new algorithm named Delay-Multiply-and-Sum (DMAS) was introduced. Using DMAS leads to lower levels of sidelobe compared to DAS, but resolution is not satisfying yet. In this paper, a novel beamformer is introduced based on the combination of Minimum Variance (MV) adaptive beamforming and DMAS, so-called Minimum Variance-Based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation leads to some terms which contain a DAS equation. It is proposed to use MV adaptive beamformer instead of existing DAS inside the DMAS algebra expansion. MVB-DMAS is evaluated numerically compared to DAS, DMAS and MV and Signal-to-noise ratio (SNR) metric is presented. It is shown that MVB-DMAS leads to higher image quality and SNR for about 13 dB, 3 dB and 2 dB in comparison with DAS, DMAS and MV, respectively.