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Blind stain decomposition for histo-pathology images using circular nature of chroma components

In this paper, we present a novel approach to achieve blind stain decomposition in histo-pathology images. The method is based on stain color estimation, followed by stain absorbing vector generation and matrix computation. Unlike conventional approaches adopting linear processing algorithms to analyze chromatic information in the cylindrical-coordinate color spaces, which may be inappropriate for circular data such as hue, we propose the use of circular thresholding on saturation-weighted hue histogram to compute candidates for stain representative colors. Experimental results suggest that our stain decomposition method is capable to address spectral variation in stains effectively. We compare the proposed method to state-of-the-art blind stain separation algorithms for nuclei segmentation on breast histo-pathology images, and demonstrate that the segmentation scheme adopting our method in its pre-processing step achieves the best segmentation results.