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This paper uses image analysis and multivariate pattern recognition techniques to segment colour microscope images of stained mammary tissue sections, with the aim of automatically identifying and counting different types of cells in the image. Results are compared for 36 classifier-colour space combinations in terms of successful identification rate of cell nuclei and visual acceptability.