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HistoStarGAN: A Unified Approach to Stain Normalisation, Stain Transfer and Stain Invariant Segmentation in Renal Histopathology
Virtual stain transfer is a promising area of research in Computational Pathology, which has a great potential to alleviate important limitations when applying deeplearningbased solutions such as lack of annotations and sensitivity to a domain shift.
Towards Measuring Domain Shift in Histopathological Stain Translation in an Unsupervised Manner
Domain shift in digital histopathology can occur when different stains or scanners are used, during stain translation, etc.
Self adversarial attack as an augmentation method for immunohistochemical stainings
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.
Towards Histopathological Stain Invariance by Unsupervised Domain Augmentation using Generative Adversarial Networks
The application of supervised deep learning methods in digital pathology is limited due to their sensitivity to domain shift.
