  It has been shown that unpaired image-to-image translation methods
constrained by cycle-consistency hide the information necessary for accurate
input reconstruction as imperceptible noise. We demonstrate that, when applied
to histopathology data, this hidden noise appears to be related to stain
specific features and show that this is the case with two immunohistochemical
stainings during translation to Periodic acid- Schiff (PAS), a histochemical
staining method commonly applied in renal pathology. Moreover, by perturbing
this hidden information, the translation models produce different, plausible
outputs. We demonstrate that this property can be used as an augmentation
method which, in a case of supervised glomeruli segmentation, leads to improved
performance.
