  We report results on unsupervised organization of cervical cells using
microscopy of Pap-smear samples in brightfield (3-channel colour) as well as
high resolution quantitative phase imaging modalities. A number of
morphological parameters are measured for each of the 1450 cell nuclei (from
$10$ woman subjects) imaged in this study. The Principal Component Analysis
(PCA) methodology applied to this data shows that the cell image clustering
performance improves significantly when brightfield as well as phase
information is utilized for PCA as compared to when brightfield-only
information is used. The results point to the feasibility of an image-based
tool that will be able to mark suspicious cells for further examination by the
pathologist. More importantly our results suggest that the information in
quantitative phase images of cells that is typically not used in clinical
practice is valuable for automated cell classification applications in general.
