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Artificial intelligence in musculoskeletal oncology imaging: A critical review of current applications

Authors :
Maxime Lacroix
Theodore Aouad
Jean Feydy
David Biau
Frédérique Larousserie
Laure Fournier
Antoine Feydy
Centre de vision numérique (CVN)
Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay
OPtimisation Imagerie et Santé (OPIS)
Inria Saclay - Ile de France
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de vision numérique (CVN)
Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-CentraleSupélec-Université Paris-Saclay
Source :
Diagnostic and Interventional Imaging, Diagnostic and Interventional Imaging, 2022, ⟨10.1016/j.diii.2022.10.004⟩
Publication Year :
2022

Abstract

Artificial intelligence (AI) is increasingly being studied in musculoskeletal oncology imaging. AI has been applied to both primary and secondary bone tumors and assessed for various predictive tasks that include detection, segmentation, classification, and prognosis. Still, in the field of clinical research, further efforts are needed to improve AI reproducibility and reach an acceptable level of evidence in musculoskeletal oncology. This review describes the basic principles of the most common AI techniques, including machine learning, deep learning and radiomics. Then, recent developments and current results of AI in the field of musculoskeletal oncology are presented. Finally, limitations and future perspectives of AI in this field are discussed.

Details

ISSN :
22115684
Volume :
104
Issue :
1
Database :
OpenAIRE
Journal :
Diagnostic and interventional imaging
Accession number :
edsair.doi.dedup.....a1c2ce4eb04ed3696ba402de0e1f5ec6
Full Text :
https://doi.org/10.1016/j.diii.2022.10.004⟩