Deep learning-based virtual staining of histological tissues (Conference Presentation)

Abstract

Histochemical staining is traditionally performed using chemical labeling, which can be time consuming and expensive, particularly when multiple stains are needed. We present a technique which can be used to virtually stain histological tissues using deep learning. As this technique is performed computationally, multiple stains can be performed on each tissue, allowing pathologists to get more information out of a single tissue section. These stains can be performed using autofluorescence images of unlabeled tissue sections, or with scans of stained H&E stained tissues, which fits into existing pathology workflows. These stains have been validated in blind studies by board-certified pathologists.