Fig. 3: Assessing performance beyond pixel level using cell-type and spatial analyses.
From: Histopathology-based protein multiplex generation using deep learning
a, Cell-typing results: ROIs from the tumour centre ((i) and (ii)) and tumour front ((iii)–(v)), showing H&E, GT and predicted cell types in ROIs grouped by their location within the tissue: tumour centre and tumour front. Scale bars, 100 μm. b, Spearman’s correlation coefficients between protein pairs, comparing the GT with both SP and MP predictions of HistoPlexer (i). The pairs on the x axis are ordered by increasing Spearman’s correlation in the GT. MSE between the GT and predicted Spearman’s correlation coefficients, comparing the SP and MP predictions of HistoPlexer (ii). Bars represent mean values, and error bars indicate standard deviation (s.d.). c, Joint t-SNE visualization of protein co-localization patterns for selected markers: CD3, CD8a, CD31, gp100 and MelanA. The colour represents normalized protein expression.
