Adaptive scaled coherence factor for ultrasound pixel-based beamforming

Area of Science:

• Medical Imaging
• Ultrasound Technology
• Signal Processing

Background:

• Synthetic aperture (SA) ultrasound imaging offers high resolution but suffers from poor signal-to-noise ratio (SNR) due to low pulse energy.
• Existing SA methods like SA with bidirectional pixel-based focusing (SA-BiPBF) are limited by nonadaptive delay-and-sum (DAS) beamforming.

Purpose of the Study:

• To introduce an adaptive scaled coherence factor (AscCF) method to improve SA-BiPBF image quality.
• To enhance SNR estimation adaptively using generalized coherence factor (GCF) for signal coherence measurement.

Main Methods:

• Proposed an adaptive scaled coherence factor (AscCF) algorithm for SA-BiPBF.
• Utilized generalized coherence factor (GCF) for adaptive parameter adjustment in SNR estimation.
• Evaluated performance through simulations and experimental comparisons with other weighting techniques.

Main Results:

• AscCF applied to SA-BiPBF significantly improved image contrast ratio (CR) by up to 48.5% in simulations and 47.76% in experiments compared to scCF.
• AscCF achieved maximal improvements in speckle signal-to-noise ratio (sSNR) of 11.28% (simulation) and 20.01% (experiment) over scCF.
• The method effectively preserved the speckle pattern while enhancing image quality.

Conclusions:

• AscCF offers a significant advancement for SA-BiPBF, enhancing image contrast and SNR.
• The technique shows potential for clinical applications, improving lesion detection and maintaining tissue texture.
• Adaptive parameter optimization is key to overcoming limitations of nonadaptive beamforming in SA ultrasound.