title: A ridge ensemble empirical mode decomposition approach to clutter rejection for ultrasound color flow imaging.
abstract: In color flow imaging, it is a challenging work to accurately extract blood flow information from ultrasound Doppler echoes dominated by the strong clutter components. In this paper, we provide an in-depth analysis of ridge ensemble empirical mode decomposition (R-EEMD) and compare it with the conventional empirical mode decomposition (EMD) framework. R-EEMD facilitates nonuniform and trial-dependent weights obtained by an optimization procedure during ensemble combination and results in less decomposition errors when compared with the conventional ensemble empirical mode decomposition techniques. A theoretic result is then extended to demonstrate that R-EEMD has an ability to solve the mode mixing problem frequently encountered in EMD and improve the decomposition performance with adequate noise strength when separating a composite two-tone signal. Based on the proposed R-EEMD framework, a novel clutter rejection filter for ultrasound color flow imaging is designed. In a series of simulations, the R-EEMD-based filter achieves a significant improvement on blood flow velocity estimation over the state-of-the-art regression filters and decomposition-based filters, such as eigen-based and EMD filters. An experiment on human carotid artery data also verifies that the R-EEMD algorithm achieves minimum clutter energy and maximum blood-to-clutter energy ratio among all the tested techniques.
authors.affiliation: Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, China. shenzyhit@gmail.com
authors.forename: Zhiyuan
authors.initials: Z
authors.lastname: Shen
authors.forename: Naizhang
authors.initials: N
authors.lastname: Feng
authors.forename: Yi
authors.initials: Y
authors.lastname: Shen
authors.forename: Chin-Hui
authors.initials: CH
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D002339:Carotid Arteries / Q000000981:diagnostic imaging / Q000502:physiology; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D012039:Regional Blood Flow; D012815:Signal Processing, Computer-Assisted; D018615:Ultrasonography, Doppler, Color / Q000379:methods*