The wall signal removal in Doppler ultrasound systems based on recursive PCA

In Doppler ultrasound (US) systems, a high-pass filter is usually employed to remove the wall component from the blood flow signal. However, this will lead to the loss of information from the low velocity flow. In this paper, an algorithm based on the principal components analysis (PCA) is proposed, in which singular value decomposition (SVD) is used to extract the main component from the mixed signals. Furthermore, the recursive process is incorporated into the PCA method to improve the performance of wall signal removal. This approach and the traditional high-pass filtering one are, respectively, applied to analyze the computer-simulated in vitro and in vivo Doppler US signals. With the proposed method, the wall signal can be removed while a large portion of low-velocity blood signal remains. Comparison experiments show that this novel approach can satisfy the requirements of Doppler US system and is practicable under a broad range of measurement conditions. Because this algorithm is based on real data, it is currently applied to unidirectional signals.