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Journal Articles British Journal of Pharmacology Year : 2021

Artificial intelligence for solid tumour diagnosis in digital pathology

Qinghe Zeng
  • Function : Author
Floriane Arbaretaz
  • Function : Author
Estelle Devêvre
  • Function : Author
Julien Calderaro
  • Function : Author
Nicolas Lomenie
  • Function : Author
Maria Chiara Maiuri
  • Function : Author


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

Dates and versions

hal-04210289 , version 1 (18-09-2023)



Christophe Klein, Qinghe Zeng, Floriane Arbaretaz, Estelle Devêvre, Julien Calderaro, et al.. Artificial intelligence for solid tumour diagnosis in digital pathology. British Journal of Pharmacology, 2021, 178 (21), pp.4291-4315. ⟨10.1111/bph.15633⟩. ⟨hal-04210289⟩
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