Improved ultrasound speckle motion tracking using nonlinear diffusion filtering

In speckle motion tracking, blood velocity magnitude and direction are estimated from speckle pattern changes between successive images based on either two-dimensional correlation or sum-absolute-difference (SAD) methods. Even though these techniques have been proven useful for flow mapping applications, they suffer from bias effects in estimation due to the presence of clutter induced from structural motion. In this work, we propose a technique for reducing the clutter effect, and hence enhancing the robustness of velocity estimation. The proposed technique relies on separating the speckle from the underlying specular structures. The basic idea is to employ a speckle reduction strategy based on nonlinear coherent diffusion filtering to obtain speckle free image of vessels from an original B-mode. Then subtracting such image from the original image, an image for speckle is obtained. Nonlinear coherent diffusion filtering has been proven successful in removing Rayleigh distributed speckle pattern resulting mainly from blood scatterers in B-mode images while preserving structural information. This allows such scattering pattern to be utilized more accurately in calculating the velocity, estimates. The proposed method is applied to obtain pure speckle images in both numerical and experimental phantoms using an ultrasound research system and velocity estimates were obtained using two-dimensional correlation.