1082-Hist2Cell: Cellular Architectures from Histology Images

Paper Talk · Jun 5, 2026 · 22m

Hist2Cell is an innovative deep learning framework designed to predict detailed cellular architectures and fine-grained cell types directly from standard H&E histology images. By utilizing a graph-transformer architecture, the model captures both local tissue features and long-range spatial correlations to map up to 80 distinct cell types without requiring expensive molecular data for every sample. Research shows that this technology achieves high accuracy in identifying cell-type abundance and spatial colocalization across diverse tissues, including lung, breast, and skin. Beyond mapping…