With the advent of digital microscopy in pathology traditional diagnostic methods are inevitably revisited and compared to arising new approaches. Image processing based solutions are developed to replace methods applied through decades. Ploidy analysis traditionally is a flow cytometry (FCM) area, but reproducing its results with computer based image processing techniques (ICM-Image Cytometry) on digitalized specimen could have a few benefits of its own. This article aims to explore the possibilities of applying image processing to this field. The process is using the type of sample used by FCM, propidium iodide stained cell nuclei. A droplet of the specimen was placed on a glass slide and digitized. We created an image processing algorithm to detect the nuclei and measure their properties to support the forming of measurement-based, objective and reproducible diagnoses. This article also introduces a simple method for quantitative validation of segmentation algorithms that helped us to prioritize the further efforts in algorithm development.