title: Eigen-based clutter filter design for ultrasound color flow imaging: a review.
abstract: Proper suppression of tissue clutter is a prerequisite for visualizing flow accurately in ultrasound color flow imaging. Among various clutter suppression methods, the eigen-based filter has shown potential because it can theoretically adapt its stopband to the actual clutter characteristics even when tissue motion is present. This paper presents a formative review on how eigen-based filters should be designed to improve their practical efficacy in adaptively suppressing clutter without affecting the blood flow echoes. Our review is centered around a comparative assessment of two eigen-filter design considerations: 1) eigen-component estimation approach (single-ensemble vs. multi-ensemble formulations), and 2) filter order selection mechanism (eigenvalue-based vs. frequencybased algorithms). To evaluate the practical efficacy of existing eigen-filter designs, we analyzed their clutter suppression level in two in vivo scenarios with substantial tissue motion (intra-operative coronary imaging and thyroid imaging). Our analysis shows that, as compared with polynomial regression filters (with or without instantaneous clutter downmixing), eigen-filters that use a frequency-based algorithm for filter order selection generally give Doppler power images with better contrast between blood and tissue regions. Results also suggest that both multi-ensemble and single-ensemble eigen-estimation approaches have their own advantages and weaknesses in different imaging scenarios. It may be beneficial to develop an algorithmic way of defining the eigen-filter formulation so that its performance advantages can be better realized.
authors.affiliation: Medical Engineering Program, The Universityof Hong Kong, Pokfulam, Hong Kong SAR. alfred.yu@hku.hk
authors.forename: Alfred
authors.initials: A
authors.lastname: Yu
authors.forename: Lasse
authors.initials: L
authors.lastname: Lovstakken
mesh_terms: D000465:Algorithms; D002339:Carotid Arteries / Q000000981:diagnostic imaging; D004452:Echocardiography; D006801:Humans; D012815:Signal Processing, Computer-Assisted; D013961:Thyroid Gland / Q000000981:diagnostic imaging; D018615:Ultrasonography, Doppler, Color / Q000379:methods*