In medical Doppler ultrasound systems, a high-pass filter which is usually employed to filter wall clutter components, will remove the information of the low velocity blood flow. To extract intact Doppler ultrasound blood signals, a novel approach is proposed based on the spatially selective noise filtration. The wall signals are firstly estimated by the spatially selective noise filtration from wavelet spatial correlation property. Then the wall clutters are exactly obtained by a wavelet threshold de-noising technique which eliminates the residual blood flow signals. Finally the intact blood flow signals are achieved by subtracting the wall signals from the mixed signals. This approach is applied to both computer simulated and in vivo carotid Doppler ultrasound signals. The experiment results show that the wavelet space based approach 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 approach is expected to be an effective method to remove the wall clutters in Doppler ultrasound systems.
A method is proposed to simulate intravascular ultrasound （IVUS） images of athero-sclerotic plaques. To accomplish the simulation of static IVUS plaque images, the ringdown and guidewire artifacts are introduced into the polar image-formation model （PIFM）, and the fibrous, lipid and calcific contents are synthesized in plaques respectively. The simulation of sequential IVUS images can be achieved by utilizing characteristics of the pulsatile artery. The results on static images demonstrate that it outperforms the PIFM method by 56.9% in terms of the correlation coefficient （CC）, and 24.3% in terms of the mutual information （MI）. The results on sequential images demonstrate that it outperforms the PIFM method by 51.0% in terms of CC, and 10.3% in terms of MI.
