Virtual staining for histology by deep learning.

Journal: Trends in biotechnology
PMID:

Abstract

In pathology and biomedical research, histology is the cornerstone method for tissue analysis. Currently, the histological workflow consumes plenty of chemicals, water, and time for staining procedures. Deep learning is now enabling digital replacement of parts of the histological staining procedure. In virtual staining, histological stains are created by training neural networks to produce stained images from an unstained tissue image, or through transferring information from one stain to another. These technical innovations provide more sustainable, rapid, and cost-effective alternatives to traditional histological pipelines, but their development is in an early phase and requires rigorous validation. In this review we cover the basic concepts of virtual staining for histology and provide future insights into the utilization of artificial intelligence (AI)-enabled virtual histology.

Authors

  • Leena Latonen
    BioMediTech and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.
  • Sonja Koivukoski
    Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland.
  • Umair Khan
  • Pekka Ruusuvuori
    BioMediTech and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.