ContriMix: Scalable stain color augmentation for domain generalization without domain labels in digital pathology

arXiv:2306.04527v4 Announce Type: replace-cross
Abstract: Differences in staining and imaging procedures can cause significant color variations in histopathology images, leading to poor generalization when deploying deep-learning models trained from a different data source. Various color augmentation methods have been proposed to generate synthetic images during training to make models more robust, eliminating the need for stain normalization during test time. Many color augmentation methods leverage domain labels to generate synthetic images. This approach causes three significant challenges to scaling such …

arxiv augmentation color cs.cv cs.lg digital domain eess.iv labels pathology scalable type