[Necessity for and construction of cytological data banks]

Analytical and quantitative cytology is based upon photometric and morphometric measurements of single cells in stained cytological specimens. It analyzes the features of single cells and cell populations with respect to their cytodiagnostic relevance. One way to do this is the establishment of learning sets of visually selected cells, and the intercomparison of unknown cells with these data sets. Difficulties arise with the visual classification of single cells from PAP-stained gynecological smears and the pooling into classes due to the considerable photometric variation from specimen to specimen. It is demonstrated, that neither for a cancer prescreening apparatus nor an interactive diagnostic machine, highly differentiated learning sets can be dispensed with. The build-up of the TUDAB learning sets and results of single cell classification, visual reclassification, as well as population analysis and specimen classification are shown.