Raman spectroscopy is a promising optical diagnostic tool that can be applied to un-stained cells in order to detect changes in molecular composition. The data collected can be described as a chemical fingerprint of the sample under investigation. Thus it is very popular in the recent times to use Raman spectroscopy in cytology to increase diagnostic sensitivity and specificity for early stage cancer. In this thesis, I introduce an automated Raman cytology system for cancer diagnostics which integrates all the hardware and software in Micro-manager and operates them in a specific order. An autofocus algorithm for unstained cells and a three-dimensional morphology recovery algorithm are also investigated and contributed to the final automated system.With increasing usage of Raman cytology systems, automation is a solution to limit data variabilities which is a major problem at the moment. In addition, a higher throughput of cellular analysis and a reduction in manpower could be expected from the proposed automation system.