Temporal Speckle Reduction for Feature Extraction in Ultrasound Images

This paper extends speckle filtering from two to three dimensions to exploit the temporal nature of speckle to improve its reduction. A motion adaptive two-dimensional least mean square (TDLMS) filter has been applied to a time series of ultrasound images and the suitability of the results for a further computer vision stage evaluated. This filter can improve images better than by direct averaging, with a major advantage that it preserves edge data and hence fine detail in dynamic images. In order to make its operation yet more suited to speckle reduction, a novel modification to the TDLMS filter is introduced that includes a median filter within its structure. Quantitative measures are used to determine the performance of the filters on speckle reduction and in regions containing edges. Results show that the TDLMS filter produces better results than direct averaging and the modified TDLMS filter improves these further, indicating the potential for further modification.