Adaptive Singular Value Decomposition-Based Hyperecho Suppression for Diagnostic Power Doppler Ultrasound Image...

Area of Science:

• Medical Imaging
• Ultrasound Technology
• Signal Processing

Background:

• Power Doppler (PD) ultrasound offers noninvasive blood flow visualization for circulation screening.
• Human arterial imaging with PD is challenging due to hyperechoic moving structures (HMSs) causing artifacts.

Purpose of the Study:

• To develop and evaluate an adaptive singular value decomposition (SVD) filtering strategy for effective HMS suppression in PD ultrasound.
• To improve the quality of human arterial imaging by reducing artifacts.

Main Methods:

• A k-means clustering algorithm segmented regions of interest in prebeamformed IQ data.
• An adaptive SVD filtering strategy was applied, tailored to different tissue types (HMS and non-HMS regions).

Main Results:

• The proposed adaptive SVD filtering effectively suppressed HMS artifacts compared to existing methods.
• Human carotid artery imaging experiments showed significant HMS suppression across cardiac cycles and imaging locations.

Conclusions:

• The adaptive SVD filtering strategy enhances PD ultrasound imaging by reducing HMS artifacts.
• This method shows promise for improved 3-D imaging of human blood vessels using PD ultrasound.