Clutter Rejection for Doppler Ultrasound Based on Blind Source Separation

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. In most cases it is very difficult to a chive a complete suppression without affecting the Doppler signal. 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 method for clutter rejection in Doppler ultrasound to subtract all the clutter so as to achieve more accurate flow estimation. We proposed a new clutter rejection based on blind source separation using principal component analysis (PCA) and independent component analysis (ICA) methods. The proposed clutter was implanted to reduce the clutter originated from moving structure and backscattered flow, beside FIR, IIR and PR. The proposed clutter rejection method presentation is quantified in simulated FR Doppler data beside real Doppler data (heart data). The result shows that the proposed method gives better clutter rejection over other present types of clutters.