||In this talk I will describe an image analysis approach I developed during my PhD for quantifying the distribution of chromatin in (light) microscope images of cell nuclei. The distribution or pattern of chromatin is influenced by both external and internal variations of the cell environment including variations associated with the cell cycle, neoplasia, and malignancy associated changes (MACs).
I will also describe the application of this approach to automated cervical cancer screening. In particular I will present empirical results that show that it is possible to detect differences in the pattern of nuclear chromatin between samples of cells from a normal Papanicolaou-stained cervical slide and those from an abnormal slide. These differences are supportive of the existence of the MACs phenomenon. These results are, to my knowledge, the first time that MACs have been reliably demonstrated in Papanicolaou stain. This is an important finding because the primary screening test for cervical cancer, the Papanicolaou test, is based on this stain.