Doppler ultrasound wall removal based on the spatial correlation of wavelet coefficients.

In medical Doppler ultrasound systems, a high-pass filter is commonly used to reject echoes from the vessel wall. However, this leads to the loss of the information from the low velocity blood flow. Here a spatially selective noise filtration algorithm cooperating with a threshold denoising based on wavelets coefficients is applied to estimate the wall clutter. Then the blood flow signal is extracted by subtracting the wall clutter from the mixed signal. Experiments on computer simulated signals with various clutter-to-blood power ratios indicate that this method achieves a lower mean relative error of spectrum than the high-pass filtering and other two previously published separation methods based on the recursive principle component analysis and the irregular sampling and iterative reconstruction, respectively. The method also performs well when applied to in vivo carotid signals. All results suggest that this approach can be implemented as a clutter rejection filter in Doppler ultrasound instruments.