Prediction of Liver Cirrhosis Using Weighted Fisher Discriminant Ratio Algorithm

Abstract

Liver diseases are one of the significant public health issues in present scenario. Liver cirrhosis is one of the leading causes of deaths due to liver related diseases. In this work, classification of normal and cirrhotic liver is done using texture analysis. Various texture features are extracted for classification. Out of all the extracted features, seven best features are identified using fisher discriminant ratio. Further, weighted fisher discriminant ratio algorithm is designed using the selected features, such that maximum accuracy and sensitivity is achieved.