The purpose of this study is to characterize the evolution of the liver diseases towards hepatocellular carcinoma (HCC), by finding the relevant textural features obtained from ultrasound images, which accurately surprise the changes of the liver tissue in the context of this evolution. For the computation of the textural features, the following methods are used: first and second order statistics, edge-based statistics, fractal-based methods and multiresolution methods; specific methods for feature-selection are applied in order to determine the exhaustive set of independent and relevant features for each evolution phase. The specific values of these parameters, corresponding to each evolution phase, will be estimated through statistical methods. We will focus on modeling the cirrhosis and hepatocellular carcinoma, but the normal state and chronic viral hepatitis (CVH) are also taken into consideration. The final purpose is that of providing a reliable method for non-invasive characterization of the evolution towards HCC, in order to prevent this malignant tumor.