Spatial Coherence Adaptive Clutter Filtering in Color Flow Imaging—Part I: Simulation Studies

The appropriate selection of a clutter filter is critical for ensuring the accuracy of velocity estimates in ultrasound color flow imaging. Given the complex spatio-temporal dynamics of flow signal and clutter, however, the manual selection of filters can be a significant challenge, increasing the risk for bias and variance introduced by the removal of flow signal and/or poor clutter suppression. We propose a novel framework to adaptively select clutter filter settings based on color flow image quality feedback derived from the spatial coherence of ultrasonic backscatter. This framework seeks to relax assumptions of clutter magnitude and velocity that are traditionally required in existing adaptive filtering methods to generalize clutter filtering to a wider range of clinically-relevant color flow imaging conditions. In this study, the relationship between color flow velocity estimation error and the spatial coherence of clutter filtered channel signals was investigated in Field II simulations for a wide range of flow and clutter conditions. This relationship was leveraged in a basic implementation of coherence-adaptive clutter filtering (CACF) designed to dynamically adapt clutter filters at each imaging pixel and frame based on local measurements of spatial coherence. In simulation studies with known scatterer and clutter motion, CACF was demonstrated to reduce velocity estimation bias while maintaining variance on par with conventional filtering.