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Review
. 2021 Nov;178(21):4291-4315.
doi: 10.1111/bph.15633. Epub 2021 Sep 13.

Artificial intelligence for solid tumour diagnosis in digital pathology

Christophe Klein  1 , Qinghe Zeng  1   2 , Floriane Arbaretaz  1 , Estelle Devêvre  1 , Julien Calderaro  3 , Nicolas Lomenie  2 , Maria Chiara Maiuri  1
Affiliations
Free article
Review

Artificial intelligence for solid tumour diagnosis in digital pathology

Christophe Klein et al. Br J Pharmacol. 2021 Nov.
Free article

Abstract

Tumour diagnosis relies on the visual examination of histological slides by pathologists through a microscope eyepiece. Digital pathology, the digitalization of histological slides at high magnification with slides scanners, has raised the opportunity to extract quantitative information due to image analysis. In the last decade, medical image analysis has made exceptional progress due to the development of artificial intelligence (AI) algorithms. AI has been successfully used in the field of medical imaging and more recently in digital pathology. The feasibility and usefulness of AI assisted pathology tasks have been demonstrated in the very last years and we can expect those developments to be applied to routine histopathology in the future. In this review, we will describe and illustrate this technique and present the most recent applications in the field of tumour histopathology. LINKED ARTICLES: This article is part of a themed issue on Molecular imaging - visual themed issue. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v178.21/issuetoc.

Keywords: artificial intelligence; cancer; convolutional neural networks; digital pathology; histopathology.

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References

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