  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 level improvement. The
quantitative results of the numerical simulations and phantom imaging show that
the proposed VCF assisted DAS method leads to 55% and 25% improvement in FWHM,
57% and 32% improvement in SNR, respectively, compared to the state-of-the-art
DAS-based methods. The results demonstrate that the proposed method can
effectively improve the reconstructed image quality and deliver satisfactory
imaging performance even with a limited number of sensor elements. The proposed
method can potentially reduce the instrumentation cost of the photoacoustic
imaging system and contribute toward the clinical translation of the modality.
