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Contrast agents are used in ultrasound imaging to enhance blood region and thereby separate the perfused area and the surrounding tissues. But unfortunately the signals backscattered from agent and tissues are still close. So it is necessary to implement signal processing to enhance the contrast echo. In this article, we apply the autoregressive model to exploit the nonlinear behavior agent properties. Then, we process the obtained pictures by a classification method followed by erosion dilatation algorithm to obtain a satisfying differentiation of the ultrasound image into two classes. The Agent to Tissue Ratio (ATR) factor is used to compare the performance of the methods, and the Fisher criterion is used to study the classification feasibility.