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Advances in the Use of Deep Learning for the Analysis of Magnetic Resonance Image in Neuro-Oncology.
Pitarch, Carla; Ungan, Gulnur; Julià-Sapé, Margarida; Vellido, Alfredo.
Afiliação
  • Pitarch C; Department of Computer Science, Universitat Politècnica de Catalunya (UPC BarcelonaTech) and Intelligent Data Science and Artificial Intelligence (IDEAI-UPC) Research Center, 08034 Barcelona, Spain.
  • Ungan G; Eurecat, Digital Health Unit, Technology Centre of Catalonia, 08005 Barcelona, Spain.
  • Julià-Sapé M; Departament de Bioquímica i Biologia Molecular and Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), 08193 Barcelona, Spain.
  • Vellido A; Centro de Investigación Biomédica en Red (CIBER), 28029 Madrid, Spain.
Cancers (Basel) ; 16(2)2024 Jan 10.
Article em En | MEDLINE | ID: mdl-38254790
ABSTRACT
Machine Learning is entering a phase of maturity, but its medical applications still lag behind in terms of practical use. The field of oncological radiology (and neuro-oncology in particular) is at the forefront of these developments, now boosted by the success of Deep-Learning methods for the analysis of medical images. This paper reviews in detail some of the most recent advances in the use of Deep Learning in this field, from the broader topic of the development of Machine-Learning-based analytical pipelines to specific instantiations of the use of Deep Learning in neuro-oncology; the latter including its use in the groundbreaking field of ultra-low field magnetic resonance imaging.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article