Work

Virtual staining for histology by deep learning

Year: 2024

Type: review

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.

Source: Trends in biotechnology

DOI: 10.1016/j.tibtech.2024.02.009

Authors: Leena Latonen, Sonja Koivukoski, Umair Khan, Pekka Ruusuvuori

Institutions: University of Eastern Finland, University of Turku

Language: English

Topic: AI in cancer detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $7,030

Funder: Academy of Finland