Extracting Doppler ultrasound blood signals using the spatially selective noise filtration algorithm

In medical Doppler ultrasound systems, a high-pass filter is usually employed to remove wall clutter components which may also remove the information of the low velocity blood flow. To extract Doppler ultrasound blood signals exactly, a novel algorithm is proposed based on the spatially selective noise filtration. The wall signals are firstly estimated by the spatially selective noise filtration from their wavelet spatial correlation. Then the wall clutters are exactly obtained through a wavelet threshold de-noising approach which can eliminate the residual blood flow signals. Finally the intact blood flow signals are achieved by subtracting the wall clutters from the mixed signals. This algorithm has been applied to both computer simulated Doppler ultrasound signals and human carotid Doppler ultrasound signals. The experiment results show that the spatially selective noise filtration algorithm can exactly extract the blood flow signals, and achieve about 45 % lower results in the mean absolute error than that of the high-pass filtering. This algorithm is expected to be an effective method to remove the wall clutters in Doppler ultrasound systems.