Noise adaptive beamforming for linear array photoacoustic imaging
Souradip Paul, Subhamoy Mandal, Mayanglambam Suheshkumar Singh

TL;DR
This paper introduces a noise-aware adaptive beamforming method for linear array photoacoustic imaging that significantly enhances image resolution, contrast, and noise suppression while reducing computational complexity and costs.
Contribution
The paper proposes the variational coherence factor (VCF), a novel adaptive weighting technique that accounts for noise variations, improving image quality over existing methods.
Findings
55% improvement in FWHM
57% enhancement in SNR
Effective with limited sensor elements
Abstract
Delay-and-sum (DAS) algorithms are widely used for beamforming in linear array photoacoustic imaging systems and are characterized by fast execution. However, these algorithms suffer from various drawbacks like low resolution, low contrast, high sidelobe artifacts and lack of visual coherence. More recently, adaptive weighting was introduced to improve the reconstruction image quality. Unfortunately, the existing state-of-the-art adaptive beamforming algorithms are computationally expensive and do not consider the specific noise characteristics of the acquired ultrasonic signal. In this article, we present a new adaptive weighting factor named the variational coherence factor (VCF), which takes into account the noise level variations of radio-frequency data. The proposed technique provides superior results in terms of image resolution, sidelobe reduction, signal-to-noise and contrast…
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