Improved ultrasound image quality with pixel-based beamforming using a Wiener-filter and a SNR-dependent coherence...

Area of Science:

• Medical imaging
• Ultrasound technology
• Signal processing

Background:

• Pixel-based beamforming assumes spherical pulses, neglecting spatiotemporal spread and limiting axial resolution.
• Existing methods do not fully account for excitation pulse length or transducer element transfer functions, impacting image quality.

Purpose of the Study:

• To propose an efficient method for improving axial resolution in pixel-based beamforming.
• To enhance image contrast and suppress artifacts in ultrasound imaging.

Main Methods:

• Extended field pattern analysis to incorporate Wiener filtering of received waveforms before coherent pixel-based beamforming.
• Designed the Wiener filter using signals from a single scatterer at the transmit focus.
• Combined beamformer output with an adaptive coherence factor based on signal-to-noise ratio.

Main Results:

• Demonstrated significant improvements in axial resolution and contrast compared to standard coherent pixel-based beamforming and synthetic aperture imaging filters.
• The proposed method showed robustness to modeling errors in experimental data.
• Validation through simulation, phantom, and in vivo studies confirmed the effectiveness of the approach.

Conclusions:

• The developed Wiener filtering and adaptive coherence factor method offers substantial improvements in axial resolution and contrast for pixel-based beamforming.
• The approach shows promise for enhancing clinical ultrasound applications by providing clearer and more detailed images.