Adaptive complementary neighboring sub-aperture beamforming for thermoacoustic imaging

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Acoustics

Background:

• Thermoacoustic imaging (TAI) quality is often degraded by strong non-coherent clutter due to the limitations of the delay-and-sum (DAS) algorithm's uniform aperture weighting.
• This clutter significantly restricts the development and clinical application of TAI technologies.

Purpose of the Study:

• To introduce an adaptive complementary neighboring sub-aperture (NSA) beamforming algorithm to overcome the limitations of DAS in TAI.
• To improve the quality and clarity of thermoacoustic images by effectively suppressing non-coherent background noise.

Main Methods:

• The NSA algorithm incorporates a coordinate system transformation for calculating the normalized cross-correlation (NCC) matrix, simplifying computations.
• Validation involved numerical simulations with a tree branch phantom, followed by phantom, ex vivo (porcine liver), and in vivo (human arm) TAI experiments using a 3 GHz system.

Main Results:

• Numerical simulations showed a significant increase in the structural similarity index (SSIM) from 0.378 for DAS to 0.755 for NSA.
• In phantom experiments, NSA improved the generalized contrast-to-noise ratio (gCNR) from 0.936 for DAS to 0.962.
• Ex vivo and in vivo results demonstrated that NSA effectively suppresses non-coherent clutter while preserving target information integrity, outperforming coherence factor (CF) weighting.

Conclusions:

• The adaptive complementary neighboring sub-aperture (NSA) algorithm effectively reduces non-coherent background noise in TAI.
• NSA ensures the completeness of target information, offering potential for high-quality thermoacoustic images and enhanced clinical utility.