Fully automated blind color deconvolution of histopathological images

Abstract

Most whole-slide histological images are stained with hematoxylin and eosin dyes. Slide stain separation or color deconvolution is a crucial step within the digital pathology workflow. In this paper, the blind color deconvolution problem is formulated within the Bayesian framework. Our model takes into account both spatial relations among image pixels and similarity to a given reference color-vector matrix. Using Variational Bayes inference, an efficient new blind color deconvolution method is proposed which provides a fully automated procedure to estimate all the unknowns in the problem. A comparison with classical and current state-of-the-art color deconvolution algorithms, using real images with known ground truth hematoxylin and eosin values, has been carried out demonstrating the superiority of the proposed approach.