A Proximal Approach for Stain Separation and Normalization of Whole-Slide Histopathological Images
Résumé
Stain variability in histopathological images presents a major obstacle to developing accurate and reliable computer-aided diagnosis systems. In this paper, we introduce a novel stain normalization framework based on a stain separation proximal algorithm. Specifically, we first propose a new stain separation method that extracts individual stain components from a given stained image. Subsequently, we perform stain normalization by aligning the separated source stains with those of a target reference image. Experimental results demonstrate that the proposed approach effectively reduces inter-image color variations while preserving the essential structural details of the tissue.
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