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Histology is a critical tool in medicine and therefore automated histology analysis could have a profound effect on health-care quality, availability, and cost. At the same time, the field provides a host of fascinating signal processing challenges. Automated image segmentation for cell analysis is generally a difficult problem due to the large variability (different microscopes, stains, cell types, cell densities and complexity of the data (possibly time-lapse images, acquired at multiple wavelengths, using multiple microscopes, and containing large numbers of cells).