Ultrasound echocardiography despeckling with non-local means time series filter
Ultrasound imaging is one of the most important instruments of modern medical imaging modalities. However, the usefulness of ultrasound imaging is degraded due to the presence of a signal-dependent noise known as speckle. Recently, lots of algorithms have been proposed for despeckling. Unfortunately, few attentions have been paid on time series of ultrasound images like echocardiography. In this paper, we address this problem by developing a time series non-local means (NLM) filter algorithm. A distance measure relevant to a speckle model is firstly introduced to take place of the Gaussian-weighted Euclidian distance according to a Bayesian formulation. By taking the information along the temporal axis into account, we further extend the NLM filter from single frame to image time series. To lighten the computational burden, a blockwise approach and a pre-classification process are used to accelerate the algorithm. In order to evaluate our method, experiments are conducted on both synthetic and in vivo ultrasound images. Experiments show that the proposed method achieves satisfactory results in terms of removing the speckle and preserving the edges and image details, compared with the state-of-the-art methods.
despeckle non-local means time series ultrasound imaging motion estimation