Detecting low intensity nuclei on propidium iodide stained digital slides

Cancer research and diagnostics is an important frontier to apply the power of computers. Image processing gains more and more territory in pathology, our current study aims to apply image cytometry to this area. One of the most fundamental methods is ploidy analysis that aims to measure the pace of proliferation in the tissue. This is proven to be a good marker of tumor presence and aggressivity. Ploidy analysis traditionally is a flow cytometry area. The samples used in our study are the same as those used in a flow cytometer: a droplet of the suspension containing stained nuclei caught on a glass slide, covered and scanned. The resulting digital sample is analyzed by an image processing algorithm to detect cell nuclei, and measure their DNA content for the ploidy analysis. This article aims to show our progress in nucleus detection on these samples, and how this improvement to the detection of low intensity nuclei affects segmentation accuracy.