Cytopathological cancer diagnoses can be obtained less invasive than histopathological investigations. Cells
containing specimens can be obtained without pain or discomfort, bloody biopsies are avoided, and the diagnosis
can, in some cases, even be made earlier. Since no tissue biopsies are necessary these methods can also be used
in screening applications, e.g., for cervical cancer. Among the cytopathological methods a diagnosis based on
the analysis of the amount of DNA in individual cells achieves high sensitivity and specificity. Yet this analysis
is time consuming, which is prohibitive for a screening application. Hence, it will be advantageous to retain, by
a preceding selection step, only a subset of suspicious specimens. This can be achieved using highly sensitive
immunocytochemical markers like p16ink4a for preselection of suspicious cells and specimens.
We present a method to fully automatically acquire images at distinct positions at cytological specimens
using a conventional computer controlled microscope and an autofocus algorithm. Based on the thus obtained
images we automatically detect p16ink4a-positive objects. This detection in turn is based on an analysis of the
color distribution of the p16ink4a marker in the Lab-colorspace. A Gaussian-mixture-model is used to describe
this distribution and the method described in this paper so far achieves a sensitivity of up to 90%.