Ultrasound liver images have characteristics such as wide dynamic range, abundant details and low contrast, which are not propitious for features extraction and pattern classification. Images enhancement algorithms based on Multi-Scale Retinex (MSR) combines the dynamic range compression with the tonal rendition at the same time. We apply three-scale Retinex model to enhance ultrasonic liver images, then extract the lightness, contrast, and entropy of the enhanced images, comparing the results with that of the usual image enhancement methods, such as histogram equalization algorithm and homomorphic filtering algorithm. Experiment results show that image enhancement algorithms based on MSR model can improve the distinguish degree of ultrasonic liver images features (contrast, entropy), and increase contrast and entropy, which is helpful to the assisted diagnosis of liver diseases.