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This paper presents a semi-automatic classification approach to evaluate steatotic liver tissues using B-scan ultrasound images. Several features have been extracted and used in three different classifiers, such as Artificial Neural Networks (ANN), Support Vector Machines (SVM) and k-Nearest Neighbors (kNN). The classifiers were trained using the 10-cross validation method. A feature selection method based on stepwise regression was also exploited resulting in better accuracy predictions. The results showed that the SVM have a slightly higher performance than the kNN and the ANN, appearing as the most relevant one to be applied to the discrimination of pathologic tissues in clinical practice

Classifier Approaches for Liver Steatosis using Ultrasound Images