Optimized Whole-Slide-Image H&E Stain Normalization: A Step Towards Big Data Integration in Digital Pathology.

ABSTRACT: In the medical diagnostics domain, pathology and histology are pivotal for the precise identification of diseases. Digital histopathology, enhanced by automation, facilitates the efficient analysis of massive amount of biopsy images produced on a daily basis, streamlining the evaluation process. This study focuses in Stain Color Normalization (SCN) within a Whole-Slide Image (WSI) cohort, aiming to reduce batch biases. Building on published graphical method, this research demonstrates a mathematical population or data-driven method that optimizes the dependency on the number of reference WSIs and corresponding aggregate sums, thereby increasing SCN process efficiency. This method expedites the analysis of color convergence 50-fold by using stain vector Euclidean distance analysis, slashing

SUBMITTER: Agraz JL 

PROVIDER: S-EPMC11573418 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature