Fig. 2
From: VISGAB: Virtual staining-driven GAN benchmarking for optimizing skin tissue histology
The top image (a) features preprocessing pipeline, highlighting various steps involved from acquisition of an unstained tissue slide to yielding of training patches. The bottom image (b) features a typical GAN architecture, highlighting its generator(s), discriminator(s), and associated loss function(s).
