Analyzing immunohistochemically stained whole-slide images of ovarian carcinoma
Bug D, Grote A, Schüler J, Feuerhake F, Merhof D (2017)
Publication Type: Conference contribution
Publication year: 2017
Journal
Publisher: Kluwer Academic Publishers
Pages Range: 173-178
Conference Proceedings Title: Informatik aktuell
Event location: Heidelberg, DEU
ISBN: 9783662543443
DOI: 10.1007/978-3-662-54345-0_41
Abstract
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.
Involved external institutions
Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen
Germany (DE)
Medizinische Hochschule Hannover (MHH) / Hannover Medical School
Germany (DE)
Charles River Laboratories International, Inc.
United States (USA) (US)
Germany (DE)
Medizinische Hochschule Hannover (MHH) / Hannover Medical School
Germany (DE)
Charles River Laboratories International, Inc.
United States (USA) (US)
How to cite
APA:
Bug, D., Grote, A., Schüler, J., Feuerhake, F., & Merhof, D. (2017). Analyzing immunohistochemically stained whole-slide images of ovarian carcinoma. In Klaus Hermann Maier-Hein, Heinz Handels, Thomas Martin Deserno, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 173-178). Heidelberg, DEU: Kluwer Academic Publishers.
MLA:
Bug, Daniel, et al. "Analyzing immunohistochemically stained whole-slide images of ovarian carcinoma." Proceedings of the Workshops on Image processing for the medicine, 2017, Heidelberg, DEU Ed. Klaus Hermann Maier-Hein, Heinz Handels, Thomas Martin Deserno, Thomas Tolxdorff, Kluwer Academic Publishers, 2017. 173-178.
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