Conference Proceeding
Authors: Thomas Janssens (KU Leuven) , An-Katrien De Roo (KU Leuven) , Beatrijs Foets (UZ Leuven) , Joost J. van den Oord (KU Leuven) , Greet Van den Berghe (KU Leuven) , Fabian Guiza (KU Leuven)
Fuchs’ endothelial corneal dystrophy (FECD) is a degenerative disease that affects the elderly population, and which lacks a unifying pathogenic theory and tangible drug targets. Immunohistochemical stainings can be used to identify proteins involved in the pathogenesis of FECD. We introduce a method for the automatic quantification of the ratio of stained cells starting from full high-resolution cornea images. First, the endothelium is extracted using entropy information in a low-resolution resampling. Then, within the endothelium, we heuristically detect and classify nuclei based on their size, color, and the color of the surrounding cytoplasm. This method achieves comparable results to manual evaluation in a set of corneas of patients with and without FECD.
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How to Cite: Janssens, T. , De Roo, A. , Foets, B. , van den Oord, J. J. , Van den Berghe, G. & Guiza, F. (2014) “Automated detection and classification of nuclei in immunohistochemical stainings for Fuchs' endothelial corneal dystrophy”, Proceedings of the Ophthalmic Medical Image Analysis International Workshop. 1(2014). doi: https://doi.org/10.17077/omia.1013