Combining autocorrelation signals with delay multiply and sum beamforming algorithm for ultrasound imaging

Area of Science:

• Medical Imaging
• Ultrasound Technology
• Signal Processing

Background:

• The delay and sum (DAS) beamforming algorithm is a standard in ultrasound imaging but offers limited resolution and contrast.
• Filtered delay multiply and sum (F-DMAS) offers improvements but still has limitations in image quality.

Purpose of the Study:

• To introduce a novel lag-based delay multiply and sum (L-DMAS) beamforming algorithm.
• To enhance the efficiency and performance of ultrasound image quality beyond existing methods.

Main Methods:

• Developed the lag-based delay multiply and sum (L-DMAS) algorithm, integrating autocorrelation signals with the delay multiply and sum (DMAS) approach.
• Utilized Field II software for simulations on point target and cyst phantoms.
• Evaluated algorithm performance using simulated, experimental, and in vivo ultrasound data.

Main Results:

• Both double stage delay multiply and sum (DS-DMAS) and L-DMAS significantly outperformed DAS and F-DMAS across all tested datasets.
• L-DMAS demonstrated superior performance compared to DS-DMAS in specific scenarios.
• The proposed L-DMAS algorithm consistently improved image quality metrics.

Conclusions:

• The L-DMAS beamforming algorithm represents a significant advancement in ultrasound imaging.
• L-DMAS offers superior resolution and contrast compared to conventional and F-DMAS methods.
• This novel approach holds promise for enhanced diagnostic capabilities in ultrasound applications.