Correlation processing for correction of phase distortions in subaperture imaging.

Area of Science:

• Medical Imaging
• Ultrasound Technology
• Signal Processing

Background:

• Ultrasonic subaperture imaging synthesizes large arrays from smaller ones for improved image quality and lower cost.
• Tissue inhomogeneities and motion introduce phase distortions, limiting subaperture imaging accuracy.
• Current phase correction methods rely on signal correlation, which can be unreliable.

Purpose of the Study:

• To explore novel correlation processing techniques for adaptive subaperture imaging.
• To develop methods for correcting phase distortions caused by motion and tissue inhomogeneities.
• To enhance the accuracy and robustness of phase correction in real-time ultrasonic imaging.

Main Methods:

• Developed new subaperture data acquisition schemes to generate reference signal sets.
• Employed correlation processing for adaptive phase correction of received echo signals.
• Utilized raw radio frequency (RF) data from two phantoms with a 3.5 MHz, 128-element transducer array.

Main Results:

• Proposed techniques demonstrated effective compensation of phase distortions.
• Real-time adaptive subaperture imaging with phase correction was achieved.
• Improved signal correlation in reference signal sets was observed.

Conclusions:

• The novel correlation processing techniques significantly improve adaptive subaperture imaging.
• Effective real-time phase correction for motion and tissue inhomogeneities is feasible.
• These advancements contribute to enhanced ultrasonic image quality and system performance.