Eigen-based clutter filter design for ultrasound color flow imaging: a review

Area of Science:

• Medical Imaging
• Ultrasound Technology
• Signal Processing

Background:

• Accurate ultrasound color flow imaging requires effective suppression of tissue clutter.
• Eigen-based filters offer adaptive clutter suppression by adjusting to tissue motion characteristics.

Purpose of the Study:

• To review and assess eigen-based filter designs for improved clutter suppression in ultrasound.
• To compare different eigen-component estimation and filter order selection methods.

Main Methods:

• Comparative assessment of single-ensemble vs. multi-ensemble eigen-component estimation.
• Evaluation of eigenvalue-based vs. frequency-based filter order selection algorithms.
• Analysis of clutter suppression in intra-operative coronary and thyroid imaging.

Main Results:

• Eigen-filters using frequency-based order selection yield superior Doppler power image contrast.
• Both single-ensemble and multi-ensemble eigen-estimation methods show distinct advantages and limitations.
• Frequency-based algorithms outperform polynomial regression filters in clutter suppression.

Conclusions:

• Optimized eigen-filter design is crucial for enhancing ultrasound flow visualization.
• Frequency-based filter order selection is key for improved contrast in Doppler power images.
• Further algorithmic development for eigen-filter formulation can unlock performance benefits.