Nuclear texture, which reflects the overall structure of the chromatin, may be used to detect early as well as later stages of malignancy. In this study, texture analysis was applied to four groups of liver cells in mice: normal and regenerating liver, hyperplastic nodules, and hepatocellular carcinomas. The best discriminating set of features was selected based on a training data set. The model was then tested on an independent series of 10 hyperplastic nodules and 6 hepatocellular carcinomas. A correct classification rate of 95% was obtained on the training data set and 100% accuracy was obtained on the test set. This kind of image analysis technique offers an opportunity to identify and describe the nuclear changes related to carcinogenesis, and the present results demonstrate the possible use of digital texture analysis as a diagnostic aid in tumor pathology.