High Dynamic Range Microscopy for Color Selective Virtual De-Staining of Immunocytological Specimens

Abstract

Immunocytochemical markers are increasingly applied for diagnosis of diseases. Usually two or more marker stains are applied at once, together with a counterstain for a reliable microscopic investigation of cell specimens. As a preprocessing step for the detection of marker-positive cells, other stains should be removed by image processing techniques. This virtual de-staining can be achieved by color separation algorithms, thus removing the undesired stain and reconstructing an image containing only the desired marker component. Known algorithms for color separation however show significant color artifacts, which are caused by inevitable non-linearities during image acquisition. In this paper we develop high dynamic range (HDR) microscopy color separation, which removes non-linearities, dynamic range limitations, as well as quantization effects and enables accurate color separation and virtual de-staining. Color accuracy in the virtual de-stained images is provided by the ΔE ₀₀ measure. Our simulations demonstrate that the perceivable color error is reduced from 86% to 0.65%. Finally, we provide results for HDR-based virtual destaining on cell samples from cytopathological routine which confirm the performance of our approach.