MLP NN Based DSS for Analysis of Ultrasonic Liver Image and Diagnosis of Liver Disease

We propose a new ultrasonic image analysis system that can be utilized as an effective tool in classifying liver states as normal, hepatitis, or liver cirrhosis. In this system, we first define suitable settings for the ultrasonic device, then remove the inhomogeneous structures from the area of interest in the image, and then, by using the forward sequential search method, look for the useful texture parameters from the co-occurrence matrix, the statistical feature matrix, the texture spectrum, and the fractal dimension descriptors. Finally, the selected parameters are fed into three different classifier i.e. MLP NN, RBF network and SVM(support vector machine) for the classification of liver disease.