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An Experimental Protocol for Assessing the Performance of New Ultrasound Probes Based on CMUT Technology in Application to Brain Imaging

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A beamforming algorithm with composite multi-conditional cross correlation and range standard deviation factor for

Qianwen Li¹, Ping Wang¹, Jinghan Chen¹

¹State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China.

The Journal of the Acoustical Society of America

|April 1, 2025

Summary

A new composite multi-conditional cross correlation and range standard deviation factor (CMCC-RSF) algorithm enhances ultrasound imaging. This method significantly improves image resolution and contrast while effectively suppressing clutter and artifacts.

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Area of Science:

Medical Imaging
Ultrasound Technology
Signal Processing

Background:

Traditional delay-and-sum (DAS) beamforming struggles with clutter suppression in ultrasound.
Coherence factor beamformers reduce clutter but can introduce dark-region artifacts.

Purpose of the Study:

To enhance ultrasound image resolution and contrast.
To develop an adaptive beamforming algorithm for superior clutter suppression and artifact reduction.

Main Methods:

Introduced the composite multi-conditional cross correlation (MCC) algorithm by integrating conditional coherence and cross-correlation factors.
Developed a range standard deviation factor (RSF) to boost MCC's resolution without compromising speckle background quality.
Evaluated the CMCC-RSF algorithm using simulations and experimental data.

Main Results:

CMCC-RSF significantly improved the full-width at half-maximum (FWHM) by up to 75.14% compared to DAS.
Maximal improvements in contrast ratio and speckle signal-to-noise ratio (SNR) reached 154.38% and 124.53%, respectively.
The algorithm demonstrated effective clutter suppression within anechoic cysts and maintained speckle background quality.

Conclusions:

The proposed CMCC-RSF algorithm offers a substantial improvement in overall ultrasound image quality.
This novel approach effectively balances clutter suppression and image resolution.
CMCC-RSF provides these benefits with relatively low computational complexity.