A histology foundation model for high-resolution spatial omics prediction, tumor detection, and, clustering of spatial transcriptomics
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Spatial transcriptomics has revolutionized biological research but is constrained by high cost and limited resolution. We present SpaFoundation, an image-only histology foundational model pre-trained on 1.79 million patches to learn general-purpose representations for spatial transcriptomics. Leveraging histology image alone and evaluated on 117 samples, our method accurately infers spatial gene expression, enhances resolution to single-cell level, outperforming state-of-the-art lightweight models, and demonstrates strong transferability to tumor detection and spatial clustering.
