Fig. 5: UNMaSk results with single-cell classification and Voronoi tessellation.

a A representative example of an adjacent DCIS case illustrating single-cell classification results in two DCIS regions. Scale bar represents 100 µm. b High-resolution images of areas within the two DCIS regions, showing single-cell classification using unified segmentation and classification pipeline based on DRDIN and SCCNN, classifying cells into the epithelial cell (green), stromal cell (yellow) and lymphocyte (blue). Scale bar represents 50 µm. c Heatmap showing lymphocyte cell density based on single-cell classification results. d Voronoi tessellation using the centres of DCIS ducts as seeds, performed over tissue region excluding epithelial cells identified by single-cell classification that was not DCIS. Because of the mathematical principles underlying Voronoi tessellations, lymphocytes within a polygon will be closer to its seed than any other seeds. This means that each lymphocyte can now be assigned to its closest DCIS duct within the tessellation space, thereby quantifying lymphocyte abundance for each DCIS duct locally. Note that because convex polygon was used, some of the DCIS ducts closer to the invasive region were omitted from the analysis. Scale bar represents 100 µm.