Digital pathology, driven by the increasing capabilities of modern computers, is an emerging field within medical research and diagnostics. A re-occurring task in pathology is the analysis of immuno-histochemical (IHC) stains, i.e. stains in which a specific type of immune cell is highlighted using corresponding antibodies. Automatic quantification of these images is a challenge due to large image sizes of up to 10 gigapixels, but provides a more objective and reproducible evaluation than the exhaustive task of manual analysis. In this context, we compare counting measures against area-based measures in the case of cytoplasmic and membrane-bound IHC stains. Our evaluation indicates a superior performance of the area-based method which reaches a Jaccard index of approximately 80%, while cell nuclei count-based approaches can be severely affected by variance due to masking effects when the cytoplasmic chromogenic staining covers the blue nuclear counterstain.
CITATION STYLE
Bug, D., Grote, A., Schüler, J., Feuerhake, F., & Merhof, D. (2017). Analyzing immunohistochemically stained whole-slide images of ovarian carcinoma. In Informatik aktuell (pp. 173–178). Kluwer Academic Publishers. https://doi.org/10.1007/978-3-662-54345-0_41
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