Computer-aided diagnostic system for diffuse liver diseases with ultrasonography by neural networks

The aim of the study is to establish a computer-aided diagnostic system for diffuse liver diseases such as chronic active hepatitis (CAH) and liver ci rrhosis (LC). We introduced an artificial neural network in the classificat ion of these diseases. In this system the neural network was trained by fea ture parameters extracted from B-mode ultrasonic images of normal liver (NL ), CAH and LC. For input data we used six parameters calculated by a region of interest (ROI) and a parameter calculated by five ROIs in each image. T hey were variance of pixel values, coefficient of variation, annular Fourie r power spectrum, longitudinal Fourier power spectrum which were calculated for the ROI, and variation of the means of the five ROIs. In addition, we used two more parameters calculated from a co-occurrence matrix of pixel va lues in the ROI. The results showed that the neural network classifier was 83.8 % in sensitivity for LC, 90.0 % in sensitivity for CAH and 93.6 % in s pecificity, and the system was considered to be helpful for clinical and ed ucational use.