In the field of histopathologic diagnosis, differential diagnosis of borderline lesions is a serious problem. Especially, differential diagnosis between early welldifferentiated hepatocellular carcinoma (ewHCC) and noncancer is difficult because the cellular atypism of ewHCC is very low. Nuclear density (number of nuclei per unit area) is one of features effective to diagnose ewHCC. In this paper, we propose new feature, degree of nuclear concentration, which represents the degree how densely nuclei are locally distributed. Two methods, counting method and density method, are proposed to quantify this feature. Counting method detects the dense regions, the regions where nuclei are densely distributed, by counting the number of nuclei in a circle. Density method converts each nuclear position to density distribution, and detects the dense regions as the regions having high density value. About 90% of correct ratio was obtained for both methods by the experiment, which shows effectiveness of this new feature. The feature was effective even if the nuclear density was normalized. Relative index, the ratio of features between ewHCC and non-cancer, was also shown to become another effective feature.