Quantitative immunohistochemistry is needed in order to reliably and accurately assess the expression of cellular proteins in tissue. Skin is a difficult tissue for automated image analysis due to its heterogeneous composition and its architecture. In the present study we used a psoriatic skin model to compare the expression of p53 and bcl-2 before and after treatment with anti-tumor necrosis factor-alpha using digital image analysis. Digital photomicrographs were acquired and analyzed with Scion image software in order to obtain the fraction of p53 and bcl-2 immunoreactive cells' area out of the total area investigated. Statistical analysis with ANOVA revealed a significant increase of p53 expression and a decrease of bcl-2 expression in all 3 epidermal layers during the course of therapy (p<0.001). The results were in line with the conventional histopathological evaluation using an arbitrary scale to grade the extent and intensity of the staining. So, the estimation of volume fraction of immunohistochemically labelled cells in skin tissue can be performed easily and rapidly using commonly available image analysis software and provides reproducible and unbiased numerical estimations of the amount of cell labelling.