Abstract

The authors investigate the use of filtering techniques to reduce speckle in ultrasound images, to improve their suitability for later feature extraction. The maximum likelihood estimator for a speckle corrupted image is shown to correspond to the statistical mode but this is difficult to determine for small populations, such as those contained by a filter mask. The truncated median filter approximates the mode by using the order of known image statistics and provides a fully automated image processing technique for speckle filtering. The filter's performance is established using a new quantitative evaluation scheme that closely considers the effect of filtering on edges, a key factor when applying features extraction in automated image interpretation. Application to in vivo and phantom test images shows that the truncated median filter provides clear images with strong edges, of quality exceeding that of other techniques. These benefits are confirmed by the application of feature extraction in arterial wall labelling

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