HisCMCL: Cross-Modal Contrastive Learning with Hierarchical Multi-Scale Fusion for Spatial Expression Prediction (opens in new tab)

AbstractMotivationHigh costs and operational complexity limit the clinical application of spatial transcriptomics (ST). Inferring ST from pathology images is a promising alternative, the core of which lies in effectively aligning image and gene expression features. However, existing models are mostly limited to single-scale and single-slice modeling. This not only fails to connect microscopic cells with macroscopic tissues but also restricts generalization due to the inability to extract cros...