Blind Source Separation for Clutter and Noise Suppression in Ultrasound Imaging: Review for Different Applications

Area of Science:

• Medical Imaging
• Signal Processing
• Acoustics

Background:

• Blind source separation (BSS) techniques are valuable for noise and clutter suppression in ultrasonic imaging.
• BSS excels where desired and undesired signals overlap spectrally, unlike traditional frequency-based filters.

Purpose of the Study:

• To review existing BSS methods for their potential in ultrasound imaging.
• To evaluate BSS effectiveness in contrast-ultrasound super-resolution, quantification, and speckle tracking.

Main Methods:

• In silico, in vitro, and in vivo testing of various BSS techniques.
• Comparison of BSS performance across different ultrasound imaging applications.

Main Results:

• BSS demonstrates significant potential for enhancing ultrasonic imaging quality.
• The selection of appropriate signal components is critical for successful BSS filtering.
• A priori domain knowledge is essential for defining effective signal component selection criteria.

Conclusions:

• BSS is a powerful tool for improving ultrasonic imaging, particularly in complex scenarios.
• Domain knowledge plays a crucial role in optimizing BSS for specific ultrasound applications.
• Further research into BSS component selection can unlock advanced capabilities in ultrasound analysis.