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Artificial intelligence for solid tumour diagnosis in digital pathology

British journal of pharmacology, 2021-11, Vol.178 (21), p.4291-4315 [Peer Reviewed Journal]

2021 The British Pharmacological Society ;2021 The British Pharmacological Society. ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0007-1188 ;EISSN: 1476-5381 ;DOI: 10.1111/bph.15633 ;PMID: 34302297

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Title:
Artificial intelligence for solid tumour diagnosis in digital pathology
Author: Klein, Christophe ; Zeng, Qinghe ; Arbaretaz, Floriane ; Devêvre, Estelle ; Calderaro, Julien ; Lomenie, Nicolas ; Maiuri, Maria Chiara
Subjects: Algorithms ; Artificial Intelligence ; cancer ; Computer Science ; convolutional neural networks ; Diagnosis ; digital pathology ; Histopathology ; Humans ; Image processing ; Image Processing, Computer-Assisted ; Information processing ; Life Sciences ; Neoplasms - diagnosis ; Pathology ; Solid tumors
Is Part Of: British journal of pharmacology, 2021-11, Vol.178 (21), p.4291-4315
Description: 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
Publisher: England: Blackwell Publishing Ltd
Language: English
Identifier: ISSN: 0007-1188
EISSN: 1476-5381
DOI: 10.1111/bph.15633
PMID: 34302297
Source: GFMER Free Medical Journals
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Artificial intelligence for solid tumour diagnosis in digital pathology

2021 The British Pharmacological Society ;2021 The British Pharmacological Society. ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0007-1188 ;EISSN: 1476-5381 ;DOI: 10.1111/bph.15633 ;PMID: 34302297

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