Noise Adaptive Beamforming for Linear Array Photoacoustic Imaging

The delay-and-sum (DAS) algorithm is widely used for beamforming in linear array photoacoustic (PA) imaging systems and is characterized by fast execution. However, these algorithms suffer from various drawbacks, such as low resolution, low contrast, high sidelobe artifacts, and lack of visual coher...

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Bibliographic Details
Published in:IEEE transactions on instrumentation and measurement 2021, Vol.70, p.1-11
Main Authors: Paul, Souradip, Mandal, Subhamoy, Singh, Mayanglambam Suheshkumar
Format: Article
Language:English
Subjects:
Adaptive algorithms
Adaptive signal processing
Algorithms
Array signal processing
Beamforming
Coherence
Image contrast
Image quality
Image reconstruction
Image resolution
Imaging
Linear arrays
linear-array imaging
Noise
Noise levels
Noise reduction
noise reduction model
photoacoustic (PA) imaging
Real-time systems
Sidelobe reduction
Sidelobes
Signal to noise ratio
Transducers
ultrasonic beamforming
Weighting
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Summary:The delay-and-sum (DAS) algorithm is widely used for beamforming in linear array photoacoustic (PA) imaging systems and is characterized by fast execution. However, these algorithms suffer from various drawbacks, such as 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 ratio (SNR), and contrast level improvement. The quantitative results of the microsphere phantom imaging show that the proposed VCF-assisted DAS method leads to 55% and 25% improvements in full-width-at-half-maximum (FWHM) and 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 PA imaging system and contribute toward the clinical translation of the modality.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2021.3103260