Fig. 1: Overview of HistoPlexer architecture.
From: Histopathology-based protein multiplex generation using deep learning
a, The HistoPlexer consists of a translator G that takes H&E and IMC images as input and predicts protein multiplexes from morphology information encoded in the H&E images, ultimately generating protein multiplex on the WSI level from H&E input. b, The objective functions of HistoPlexer contain the GAN adversarial loss (i), Gaussian pyramid loss with average L1 distance across scales (ii), and patch-wise contrastive loss with anchor from generated IMC and positive and negative from GT IMC (iii).
