On the performance of regression and step-initialized IIR clutter filters for color Doppler systems in diagnostic medical ultrasound

Abstract

One of the major issues in color Doppler ultrasound is the suppression of clutter that arises from stationary or slowly moving tissue. If not adequately suppressed, clutter can severely affect the ability of color Doppler systems to accurately estimate the Doppler mean frequency and power of blood, resulting in a potentially misleading depiction of flow. In this study, the performances of two classes of clutter suppression techniques-step-initialized infinite impulse response (IIR) and regression filters-were evaluated and compared by means of extensive simulations. The performance indicators used were the accuracy and precision of the mean frequency and the power estimates after clutter filtering. In summary, the ability of both filter classes to suppress clutter was found to vary considerably depending on factors such as the clutter-to-flow-signal ratio and the ensemble length. In particular, the performance of step-initialized IIR filters was shown to be noticeably inferior to that predicted by their steady-state response. Regression filters were found to offer significantly better performance than step-initialized IIR filters under heavy clutter conditions and, given their steeper roll-off, appear to be more effective clutter suppressors for power Doppler imaging. However, it should be noted that, as demonstrated by the simulations, the performance of IIR filters is severely degraded by their transient response which, in turn, is determined by the initialization scheme used. Therefore, more elaborate schemes-with superior transient characteristics than step-initialization-could significantly improve the effectiveness of IIR filtering under heavy clutter conditions.<>