High throughput image cytometers analyze individual cells in digital photomicrographs by first assigning pixels within each image to plasma membrane, cytoplasm, nucleus, or other regions. In this study, we report on a novel algorithm that: 1) identifies plasma membrane regions to measure changes in plasma membrane-associated proteins (protein kinase C [PKC] alpha, N-cadherin, E-cadherin, vascular endothelium [VE]-cadherin, and pan-cadherin) that regulate cell division, migration, and adhesion and 2) delineates the cell for generalized three-compartment image cytometry. Validation assays were performed for these proteins on cells cultured in 96-well plates and also for tissue sections obtained from transgenic and chemical carcinogenic models of skin cancer. The algorithm successfully quantified phorbol 12-myristate 13-acetate (PMA)-induced plasma membrane localization of PKCalpha in HeLa cells (Z' of 0.88). Additionally, PMA activated translocation to the plasma membrane at P < .01 of N-cadherin (in HeLa cells), E-cadherin (in A431 cells), and VE-cadherin (in human dermal microvascular endothelial cells), suggesting a relationship between PKCalpha activity and cadherin localization. For VE-cadherin, a Z' of 0.52 was obtained between serum-free medium, which increased VE-cadherin, and EGTA, which diminished VE-cadherin at the plasma membrane. For sections obtained from the transgenic skin cancer model, analysis of images with the plasma membrane algorithm revealed that tumor cells exhibited cadherin expression that was just 34% of that expressed by surrounding normal tissue; furthermore, tumor cells expressed elevated DNA content, consistent with development of aneuploidy. In contrast, increased DNA content did not occur for tumor cells produced by chemical carcinogenesis. The results demonstrate that this new algorithm for plasma membrane image cytometry enables statistically significant analyses in a variety of applications in both cultured cells and tissue sections.