Enhanced Linear-array Photoacoustic Beamforming using Modified Coherence Factor

TL;DR

This paper introduces a modified coherence factor (MCF) for linear-array photoacoustic imaging that improves image resolution and contrast by replacing the DAS algebra with DMAS in the weighting process, validated through numerical and experimental results.

Contribution

It proposes a novel MCF technique that enhances photoacoustic image quality by integrating DMAS into the coherence factor calculation, outperforming traditional CF.

Findings

MCF reduces sidelobes compared to CF.

MCF improves SNR by approximately 45%.

MCF enhances resolution with about 40% better FWHM.

Abstract

Photoacoustic imaging (PAI) is a promising medical imaging modality providing the spatial resolution of ultrasound (US) imaging and the contrast of pure optical imaging. For linear-array PAI, a beamformer has to be used as the reconstruction algorithm. Delay-and-sum (DAS) is the most prevalent beamforming algorithm in PAI. However, using DAS beamformer leads to low resolution images along with significant effects of the off-axis signals. Coherence factor (CF) is a weighting method in which each pixel of the reconstructed image is weighted, based on the spatial spectrum of the aperture, to improve the contrast. In this paper, it has been shown that the numerator of the formula of CF contains a DAS algebra, and it was proposed to use the delay-multiply-and-sum (DMAS) beamformer instead of the available DAS on the numerator. The proposed weighting technique, modified CF (MCF), has been evaluated numerically and experimentally compared to CF, and it was shown that MCF leads to lower sidelobes and better detectable targets. The quantitative results of the experiment (using wire targets) show that MCF leads to for about 45% and 40% improvement, in comparison with CF, in the terms of signal-to-noise ratio and full-width-half-maximum, respectively.