Generative Adversarial Networks for Stain Normalisation in Histopathology

arXiv:2308.02851v2 Announce Type: replace-cross
Abstract: The rapid growth of digital pathology in recent years has provided an ideal opportunity for the development of artificial intelligence-based tools to improve the accuracy and efficiency of clinical diagnoses. One of the significant roadblocks to current research is the high level of visual variability across digital pathology images, causing models to generalise poorly to unseen data. Stain normalisation aims to standardise the visual profile of digital pathology images without changing the structural content of …

abstract accuracy adversarial artificial artificial intelligence arxiv clinical cs.cv cs.lg current development digital eess.iv efficiency generative generative adversarial networks growth intelligence networks pathology research tools type visual