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Train and evaluate histology models on STHELAR with a leave-one-tissue-out (LOTO) protocol. Demonstrate that a domain-generalization (DG) approach reduces the performance collapse on unseen organs compared to a baseline (CellViT/ViT/UNet).
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Cross Tissue Generalization using the LOTO (Leave One Tissue Out) approach on hematoxylin and eosin stained tissue samples. Using the STHELAR dataset created by MICS-Lab at Paris-Saclay University.