A Single-Ensemble Clutter Rejection Method Based on the Analytic Geometry for Ultrasound Color Flow Imaging

Abstract

In ultrasound color flow imaging (CFI), the single-ensemble eigen-based filters can reject clutter components using each slow-time ensemble individually. They have shown excellent spatial adaptability. This article proposes a novel clutter rejection method called the single-ensemble geometry filter (SGF), which is derived from an analytic geometry perspective. If the transmitted pulse number M equals two, the clutter component distribution on a two-dimensional (2-D) plane will be similar to a tilted ellipse. Therefore, the direction of the major axis of the ellipse can be used as the first principal component of the autocorrelation matrix estimated from multiple ensembles. Then the algorithm is generalized from 2-D to a higher dimensional space by using linear algebra representations of the ellipse. Comparisons have been made with the high-pass filter (HPF), the Hankel-singular value decomposition (SVD) filter and the recursive eigen-decomposition (RED) method using both simulated and human carotid data. Results show that compared with HPF and Hankel-SVD, the proposed filter causes less bias on the velocity estimation when the clutter velocity is close to that of the blood flow. On the other hand, the proposed filter does not need to update the autocorrelation matrix and can achieve better spatial adaptability than the RED.