6 March 2018 Color deconvolution method with DAB scatter correction for bright field image analysis
Author Affiliations +
For histochemical staining, to highlight multiple biomarkers within a sample, multiple stains with different light spectral absorption characteristics are deployed (i.e. multiplexing). To reconstruct the single stain contrast from a multiplexed sample, the conventional color deconvolution method assumes that light extinction follows Lambert-Beer’s law during imaging process and the optical density (OD) measured from the image is linearly related to the stain amount. However, this assumption does not hold well for commonly used diaminobenzidine (DAB) stain due to its precipitate-forming reaction during sample processing. Besides absorption, scattering also contributes to the light extinction process which causes the non-linear relation between the OD value and the stain amount. Therefore, using the conventional method may not have sufficient accuracy for quantified stain analysis, especially when DAB presents at high concentration levels. In this paper, our study shows that DAB presents different chromatic properties at different concentration levels. Therefore, we propose a new color deconvolution method to address the issue by employing a set of reference colors vectors, each of which characterizes a DAB concentration level. Then, the reference color vector that best represents the true DAB concentration level in the mixture is automatically selected for color deconvolution. Both visual and quantified assessments are provided to show that the method enables detection for a broader dynamic range of DAB concentration and therefore should be preferred by the user for bright field image analysis.
Conference Presentation
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Yao Nie, Yao Nie, Christian Roessler, Christian Roessler, Emilia Andersson, Emilia Andersson, Oliver Grimm, Oliver Grimm, "Color deconvolution method with DAB scatter correction for bright field image analysis ", Proc. SPIE 10581, Medical Imaging 2018: Digital Pathology, 105810K (6 March 2018); doi: 10.1117/12.2293576; https://doi.org/10.1117/12.2293576

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