title: Adaptive clutter filtering for ultrasound color flow imaging.
abstract: In this article, we present an adaptive clutter rejection method for selecting different clutter filters in ultrasound color flow imaging. A single clutter filter is typically used to reject the clutter. Because the clutter characteristics vary in both space and time, the single clutter filter approach has difficulty in providing optimum clutter rejection in ultrasound images. To achieve more accurate velocity estimation, we have developed a method to select a clutter filter adaptively at each location in an image from a set of predefined filters. Selection criteria have been developed based on the underlying clutter characteristics and the properties of various filters (e.g., minimum-phase finite impulse response, projection-initialized infinite impulse response and polynomial regression). We have incorporated our adaptive clutter rejection method in an ultrasound system. We have found that our adaptive method can reduce the mean absolute error between the estimated and true flow velocities significantly compared with the conventional methods, in which a single clutter filter is used throughout the entire image. With in vivo abdominal data, we obtained an average gain of 5.0 dB in signal-to-clutter ratio (SCR), compared with the conventional method. These preliminary results indicate that the proposed adaptive method could improve the accuracy of flow velocity estimation in ultrasound color flow imaging through the improvement in SCR and the reduction in bias.
authors.affiliation: Image Computing Systems Laboratory, Department of Bioengineering, University of Washington, Seattle, WA 98195-2500, USA.
authors.forename: Yang Mo
authors.initials: YM
authors.lastname: Yoo
authors.forename: Ravi
authors.initials: R
authors.lastname: Managuli
authors.forename: Yongmin
authors.initials: Y
authors.lastname: Kim
mesh_terms: D000465:Algorithms; D001783:Blood Flow Velocity; D001808:Blood Vessels / Q000000981:diagnostic imaging* / Q000502:physiology; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D018615:Ultrasonography, Doppler, Color / Q000379:methods*