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Present study proposes a computer-aided diagnostic system to assist radiologists in identifying focal liver lesions in B-mode ultrasound images. The proposed system can be used to discriminate focal liver diseases such as Cyst, Hemangioma, Hepatocellular carcinoma and Metastases, along with Normal liver. The study is performed with 111 real ultrasound images comprising of 65 typical and 46 atypical images, which were taken from 88 subjects. These images are first enhanced and then regions of interest are segmented into 800 non-overlapping segmented regions-of-interest. Subsequently 208-texture based features are extracted from each segmented region-of-interest. A two step neural network classifier is designed for classification of five liver image categories. In the first step, a neural network classifier gives classification among five liver image categories. If neural network decision is for more than one …