By means of statistical pattern recognition procedures, a quantitative description of the ultrasound B-scan images of experimental diffuse liver disease has been carried out. Fatty livers, fatty fibrosis/cirrhosis, and cirrhosis without fatty infiltration of the liver were studied in female Wistar rats. Separation accuracies of more than 80% between the tissue classes "normal" vs "fatty infiltration," or "normal" vs "fatty cirrhosis," using only two statistical image parameters were found. A subclassification of the diffuse parenchymal liver disease was not possible. It is shown by multiple linear regression analysis that the image parameter "mean grey level" correlates better with total lipid content than with the amount of connective tissue. Furthermore it is demonstrated that connective tissue leads only to a weak increase in "mean grey level," whereas the addition of connective tissue to a given tissue lipid can lead to a reduction in image brightness.