Literature DB >> 34302297

Artificial intelligence for solid tumour diagnosis in digital pathology.

Christophe Klein1, Qinghe Zeng1,2, Floriane Arbaretaz1, Estelle Devêvre1, Julien Calderaro3, Nicolas Lomenie2, Maria Chiara Maiuri1.   

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.
© 2021 The British Pharmacological Society.

Entities:  

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

Mesh:

Year:  2021        PMID: 34302297     DOI: 10.1111/bph.15633

Source DB:  PubMed          Journal:  Br J Pharmacol        ISSN: 0007-1188            Impact factor:   8.739


  2 in total

Review 1.  [Oncological surgery in the interdisciplinary context-On the way to personalized medicine].

Authors:  Lena-Christin Conradi; Michael Ghadimi
Journal:  Chirurg       Date:  2022-02-24       Impact factor: 0.955

2.  Deep learning for necrosis detection using canine perivascular wall tumour whole slide images.

Authors:  Taranpreet Rai; Ambra Morisi; Barbara Bacci; Nicholas J Bacon; Michael J Dark; Tawfik Aboellail; Spencer Angus Thomas; Miroslaw Bober; Roberto La Ragione; Kevin Wells
Journal:  Sci Rep       Date:  2022-06-23       Impact factor: 4.996

  2 in total

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