Automated classification of liver disorders using ultrasound images.

ABSTRACT

This paper presents a novel approach for detection of Fatty liver disease (FLD) and Heterogeneous liver using textural analysis of liver ultrasound images. The proposed system is able to automatically assign a representative region of interest (ROI) in a liver ultrasound which is subsequently used for diagnosis. This ROI is analyzed using Wavelet Packet Transform (WPT) and a number of statistical features are obtained. A multi-class linear support vector machine (SVM) is then used for classification. The proposed system gives an overall accuracy of ~95% which clearly illustrates the efficacy of the system.