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This paper presents an adaptive edge enhancement algorithm for ultrasound imaging. Most of classical edge enhancement techniques take the whole image as a unit and use the spatial or frequency domain edge operators to enhance the region whose grey varies largely. Because of the speckle noises of the ultrasound images, edge operators may enhance the speckles and degrade the contrast resolution of the image. Moreover, classical edge enhancement techniques can enhance the reverberation artifacts which appear like the edge. In this paper we present a segmentation method, i.e. seeking the regions whose edges needs to be enhanced and ruling out the error edges caused either by speckle noises or the reverberation artifacts. Segmentation techniques are based on the texture analysis of the spatial grey level cooccurrence matrix. The proposed enhancement function is a class of modified sigmoid functions. Results show that we can leave speckle/reverberation unchanged and enhance tissue boundaries.