A quantitative ultrasonic image evaluation system that generates a numerical severity measurement to assess the progression of chronic liver disease and assist clinical diagnosis is proposed in this paper. The progression of chronic liver disease is closely related to the amount of fibrosis of the liver parenchyma under microscopic examination. The powerful index, computer morphometry (CM) score developed in Sun et al. [Sun YN, Horng MH, Lin XZ. Automatic computer morphometry system techniques and applications in medical diagnosis. In: Cornelius TL, editor. Computational methods in biophysics, biomaterials, biotechnology and medical systems. Algorithm development, mathematical analysis and diagnostics, vol. 4. Boston/Dordrecht/London: Kluwer Academic Publishers; 2003. p. 33-50], accurately measures the fibrosis ratio of liver parenchyma from a microscopy of human liver specimens. Therefore, the results of the CM score of patients serves as an assessment basis for developing the disease measurement of the B-mode liver sonogram under echo-texture feature analysis methods. The radial basis function (RBF) network is used to establish the correlates between texture features of ultrasonic liver image and the corresponding CM score. The output of the RBF network is called the ultrasonic disease severity (UDS) score. The correct classification rate of 120 test images by using the UDS score is 92.5%. These promising results reveal that the UDS is capable of providing an important reference to diagnose chronic liver disease.