Laplacian pyramid based non-linear coherence diffusion for real-time ultrasound image speckle reduction

Abstract The inherent speckle noise in medical ultrasound image degrades valuable clinical information and affects the diagnosis quality. Therefore, commercial ultrasound systems always face a big challenge to improve the visual quality of ultrasound images by reducing the speckle noise. A new hybrid algorithm is proposed in the present paper for speckle reduction by combining nonlinear coherence diffusion (NCD) with pyramid-transform-based multi-scale filters (named as Laplacian Pyramid Based Non-linear Coherence Diffusion; viz. LPNCD). The new approach exhibits good capability in preserving tissue features while enhancing the coherence. The theory and implementation of the approach are presented and verified based on phantom and clinical data. By comparing with previous techniques on quantified signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), the results suggest that the LPNCD method may demonstrate superior performance than other commonly used AD-class filters. Meanwhile, the performance of GPU implementations of the current technique is also evaluated, and it is verified that the LPNCD approach may have good performance efficiency and wonderful visual effect as running on mainstream commercial ultrasound systems.