Abstract: In this study, the ultrasound liver images are studied to build a computer-aided automatic early detection system for the identification of cysts, tumors and cancers by analyzing their unique echo texture patterns using a custom designed back propagation neural network classifier. The texture features are extracted using various statistical and spectral methods. Then the optimal feature selection process is carried out manually to select the best discriminating features from the extracted texture parameters. Then the neural network has been designed and the optimal neural network parameters have been selected to increase the classifier performance.