EpidermaQuant: Unsupervised detection and quantification of epidermal differentiation markers on H-DAB-stained images of reconstructed human epidermis
CoRR(2024)
Abstract
The integrity of the reconstructed human epidermis generated in vitro could
be assessed using histological analyses combined with immunohistochemical
staining of keratinocyte differentiation markers. Computer-based analysis of
scanned tissue saves the expert time and may improve the accuracy of
quantification by eliminating interrater reliability issues. However, technical
differences during the preparation and capture of stained images and the
presence of multiple artifacts may influence the outcome of computational
methods. Using a dataset with 598 unannotated images showing cross-sections of
in vitro reconstructed human epidermis stained with DAB-based
immunohistochemistry reaction to visualize 4 different keratinocyte
differentiation marker proteins (filaggrin, keratin 10, Ki67, HSPA2) and
counterstained with hematoxylin, we developed an unsupervised method for the
detection and quantification of immunohistochemical staining. The proposed
pipeline includes the following steps: (i) color normalization to reduce the
variability of pixel intensity values in different samples; (ii) color
deconvolution to acquire color channels of the stains used; (iii) morphological
operations to find the background area of the image; (iv) automatic image
rotation; and (v) finding markers of human epidermal differentiation with
clustering. Also, we created a method to exclude images without DAB-stained
areas. The most effective combination of methods includes: (i) Reinhard's
normalization; (ii) Ruifrok and Johnston color deconvolution method; (iii)
proposed image rotation method based on boundary distribution of image
intensity; (iv) k-means clustering using DAB stain intensity. These results
should enhance the performance of quantitative analysis of protein markers in
reconstructed human epidermis samples and enable comparison of their spatial
distribution between different experimental conditions.
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