Advances in the Use of Deep Learning for the Analysis of Magnetic Resonance Image in Neuro-Oncology

Research output: Contribution to journalReview articleResearchpeer-review

1 Downloads (Pure)

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.
Original languageEnglish
Article number300
Number of pages55
JournalCancers
Volume16
Issue number2
DOIs
Publication statusPublished - 10 Jan 2024

Keywords

  • machine learning
  • Neurooncology
  • radiology
  • deep learning
  • data analysis pipeline
  • ultra-low field magnetic resonance imaging
  • glioma
  • glioblastoma

Fingerprint

Dive into the research topics of 'Advances in the Use of Deep Learning for the Analysis of Magnetic Resonance Image in Neuro-Oncology'. Together they form a unique fingerprint.

Cite this