Estimation and compensation of ultrasonic wavefront distortion using a blind system identification method

Area of Science:

• Medical Imaging
• Ultrasound Technology
• Signal Processing

Background:

• Wavefront aberration significantly degrades image quality in ultrasonic b-scan imaging.
• Accurate estimation and correction of these aberrations are crucial for diagnostic clarity.

Purpose of the Study:

• To introduce a novel common random input filter model for estimating and correcting wavefront aberration in ultrasound imaging.
• To enhance both transmit and receive focusing capabilities in b-scan systems.

Main Methods:

• A linear filter bank models aberration, driven by a common random signal.
• A two-level extension of subspace methods is used for blind system identification.
• Receive waveforms are compensated with inverse filtering; transmit waveforms are predistorted using time reversal.

Main Results:

• Experiments with a 2D array system demonstrated improved transmit and receive focus through a human abdominal wall phantom.
• The model successfully imaged a random medium mimicking liver tissue.
• Performance surpassed conventional time-shift and backpropagation-based compensation methods.

Conclusions:

• The proposed random input filter model offers a robust solution for wavefront aberration correction in ultrasound.
• This technique enhances focusing, leading to superior image quality in medical ultrasound applications.