Statistical pattern recognition procedures allow a quantitative description of ultrasound-B-scan image texture. According to well-established animal models, different types of fatty liver disease were induced in female Wistar rats. For the correlation of the computerized ultrasound image with its underlying histology a variable tissue model based on histomorphological data, texture analysis of the histological image and biochemical measurements of total lipid, water and hydroxyproline content was created. Whereas a regional arrangement of large fat deposits leads to a significant increase in the "mean grey level" (measure of image brightness) of the ultrasound-B-scan image, there is no difference in image brightness between normal liver tissue and liver steatosis for the tissue model with diffuse homogeneous fatty infiltration. It is demonstrated by multiple linear regression analysis that the "mean grey level" of the ultrasound-B-scan image depends not only on total lipid content but even more on the histomorphological fat deposit distribution.