An Improved Method for Cirrhosis Detection Using Liver´s Ultrasound Images

This paper describes an improved method for cirrhosis detection in the liver using Gabor features from ultrasound images. There are three main contributions of our cirrhosis detection method. The first contribution of this method is to combine weak classifiers using the AdaBoost algorithm. The second one is to use an artificial dataset to avoid the problem of over fitting the limited training dataset. The third one is to apply a voting classification with use of multiple regions of interest (ROIs). Although the accuracy rate of a single classifier designed with only original dataset was 56%, that of the proposed method was 80% in cross-validation.