A differential blood cell count represents a substantial component of the daily clinical routine. The aim of this study was to conduct automated high-throughput analyses of light microscopy images of leukocytes with unspecific staining (hematoxylin-eosin, HE) and to classify the resulting subgroups (lymphocytes, monocytes and neutrophils). Materials and Method: The software package CellProfiler was used for the image analysis and cell classification. The results were compared to those from

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... ological laboratories that analyzed the same samples. Results: There was a high similarity between the results obtained by image analysis and those from the hematological laboratories, with an r 2 =0.95 for the differential count and an r 2 =0.89 for the total count. Conclusion: Differential blood cell count using light microscopy, nonspecific dyes and advanced image analysis is accurate, reproducible, and less expensive compared to other techniques. The results also showed a strong correlation when compared to traditional methods.