Figure 4.
Top row: Supervised single-cell validation, with annotation maps generated from three labelled equine asthma WSIs where each colour represents one class of cells. Bottom row: UMAP14 dimensionality reduction approach in an unsupervised setting. The segmented equine asthma cells are first classified. Then, features for each cell are extracted. Afterwards, the high-dimensional features are transformed into a two-dimensional representation and visualised in a new image. Both approaches allow the user to verify and enhance the automatic classification results.