A new clutter rejection technique for Doppler ultrasound signal based on principal and independent component analyses

Doppler ultrasound is widely used diagnostic tool for measuring and detecting blood flow. To get a Doppler ultrasound spectrum image with a good quality, the clutter signals generated from stationary and slowly moving tissue must be removed completely. Without enough clutter rejection, low velocity blood flow cannot be measured, and estimates of higher velocities will have a large bias. Usually finite impulse response FIR, infinite impulse response IIR and polynomial regression PR filters were used for cluttering. In this paper we proposed a new clutter rejection based on principal component analysis (PCA) and independent component analysis (ICA). The proposed clutter rejection method presentation is quantified in simulated FR Doppler data beside real Doppler data. The result shows that the proposed method gives better clutter rejection.