Adaptive multi-element synthetic aperture imaging with motion and phase aberration correction.

Area of Science:

• Ultrasound imaging
• Medical imaging physics
• Signal processing

Background:

• Multi-element synthetic aperture imaging offers good image quality with simple hardware.
• However, it is prone to motion and phase aberration artifacts.
• Existing methods struggle to fully correct these aberrations.

Purpose of the Study:

• To develop an adaptive beamforming technique for multi-element synthetic aperture imaging.
• To mitigate motion and phase aberration artifacts using correlation processing.
• To enhance image quality in challenging imaging scenarios.

Main Methods:

• Exploration of correlation processing utilizing fully common spatial frequencies of overlapping subapertures.
• Analysis of signal correlation coefficients derived from common spatial frequencies versus entire subapertures.
• Testing adaptive multi-element synthetic aperture imaging on experimental radiofrequency (RF) data from a diffuse scattering phantom.

Main Results:

• Signals from common spatial frequencies showed significantly higher correlation coefficients.
• Correlation coefficient decreased linearly with subaperture separation for full subapertures, but remained constant for common frequencies.
• The adaptive method efficiently corrected motion and phase aberrations in experimental data.

Conclusions:

• Common spatial frequencies are efficient for correlation processing in adaptive synthetic aperture imaging.
• This technique effectively corrects motion and phase aberrations.
• The approach enhances the robustness and quality of multi-element synthetic aperture imaging.