Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming...

Area of Science:

• Photoacoustic Imaging
• Medical Imaging
• Signal Processing

Background:

• Delay-and-Sum (DAS) beamforming in photoacoustic imaging offers simple implementation but suffers from poor resolution and high sidelobes.
• Delay-Multiply-and-Sum (DMAS) was developed to reduce sidelobes but requires further resolution improvement.

Purpose of the Study:

• To introduce and evaluate a Minimum Variance-based Delay-Multiply-and-Sum (MVB-DMAS) beamformer.
• To enhance image resolution and reduce sidelobes in photoacoustic imaging.

Main Methods:

• Developed MVB-DMAS by integrating Minimum Variance (MV) adaptive beamforming with DMAS.
• Evaluated the MVB-DMAS algorithm through numerical simulations and experimental imaging.

Main Results:

• MVB-DMAS achieved significant sidelobe reduction: 31 dB vs DAS, 18 dB vs MV, and 8 dB vs DMAS at 45 mm depth.
• Simulations showed substantial improvements in Full-Width-Half-Maximum (96% vs DAS, 94% vs DMAS, 45% vs MV) and SNR (89% vs DAS, 15% vs DMAS, 35% vs MV).
• Experimental results demonstrated a 20 dB sidelobe reduction with MVB-DMAS at 33 mm depth compared to other methods.

Conclusions:

• MVB-DMAS offers superior performance in photoacoustic imaging compared to DAS, DMAS, and MV beamformers.
• The proposed method effectively improves image resolution and signal quality, crucial for diagnostic accuracy.