Shear Wave Speed estimator using Continuous Wavelet Transform for Crawling Wave Sonoelastography.

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Ultrasound Technology

Background:

• Crawling Wave Sonoelastography (CWS) uses ultrasound to measure tissue stiffness via Shear Wave Speed (SWS).
• Existing SWS estimators face limitations like artifacts, border effects, high computational costs, and challenges with in vivo applications.
• A need exists for improved SWS estimation techniques in CWS.

Purpose of the Study:

• To introduce and evaluate a novel SWS estimator for CWS based on the Continuous Wavelet Transform (CWT).
• To assess the performance of the CWT-based SWS estimator against established methods like Phase Derivative (PD) and Regularized Wavelength Average Velocity Estimator (R-WAVE).

Main Methods:

• Developed a new SWS estimator utilizing the Continuous Wavelet Transform (CWT).
• Acquired experimental data using a gelatin phantom with a circular inclusion, excited by dual vibration sources at varying frequencies (200-360 Hz).
• Compared CWT-derived SWS images with PD and R-WAVE methods, analyzing SWS values, coefficient of variation, and contrast-to-noise ratio.

Main Results:

• The CWT estimator generated stable SWS images across video frames.
• CWT showed comparable SWS values to PD and R-WAVE in both inclusion and background regions.
• CWT demonstrated the lowest coefficient of variation and highest contrast-to-noise ratio for most tested frequencies, enhancing region discrimination.

Conclusions:

• The proposed CWT-based SWS estimator is a viable and effective tool for CWS.
• This method offers improved image quality and accuracy, potentially overcoming limitations of existing techniques.
• The CWT estimator shows promise for characterizing soft tissues and detecting lesions in clinical settings.