Effective Hyper-clutter Artifacts Suppression for Ultrafast Ultrasound Doppler Imaging

Area of Science:

• Medical Imaging
• Ultrasound Technology
• Signal Processing

Background:

• Hyper-clutter artifacts (HCA) degrade ultrafast ultrasound Doppler imaging quality.
• HCA obscure small vessel flow signals, particularly in challenging fascial regions like the renal capsule.
• Existing methods struggle to effectively remove HCA without compromising diagnostic information.

Purpose of the Study:

• To introduce and validate the U-profile-based decluttering (UPBD) method for HCA suppression.
• To demonstrate UPBD's effectiveness in improving signal clarity in ultrafast Doppler imaging.
• To provide a computationally efficient and easily integrated solution for HCA removal.

Main Methods:

• UPBD utilizes singular value decomposition (SVD)-derived spatial singular vectors (U).
• It analyzes pixel intensity profiles along the singular-order dimension to compute a clutter-energy ratio.
• A spatially adaptive weighting map is generated and applied to SVD-filtered flow signals.

Main Results:

• UPBD significantly improved contrast-to-noise ratio (CNR) and contrast-to-tissue ratio (CTR) in vivo.
• Demonstrated substantial CTR enhancements in pig and human kidney datasets, as well as 3D human liver imaging.
• Quantitative results showed marked improvements over conventional SVD filtering techniques.

Conclusions:

• UPBD effectively suppresses HCA while preserving crucial blood flow signals.
• The method requires minimal extra computation and no extensive parameter tuning.
• UPBD offers a lightweight, integrable post-processing solution for enhanced ultrafast Doppler imaging applications.