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@ARTICLE{Galldiks:890309,
      author       = {Galldiks, Norbert and Zadeh, Gelareh and Lohmann, Philipp},
      title        = {{A}rtificial {I}ntelligence, {R}adiomics, and {D}eep
                      {L}earning in {N}euro-{O}ncology},
      journal      = {Neuro-oncology advances},
      volume       = {2},
      number       = {$Supplement_4$},
      issn         = {2632-2498},
      address      = {Oxford},
      publisher    = {Oxford University Press},
      reportid     = {FZJ-2021-00882},
      pages        = {iv1 - iv2},
      year         = {2021},
      abstract     = {Besides the histomolecular evaluation of tissue samples
                      obtained from resection or biopsy, neuroimaging forms the
                      basis for the diagnosis of brain cancer. Contrast-enhanced
                      MRI is the method of choice for brain tumor diagnostics,
                      treatment planning, and follow-up. Currently, advanced MRI
                      techniques as well as amino acid PET are increasingly
                      applied, generating a large variety of imaging parameters
                      for brain tumor diagnostics. This is also driven by the
                      increasing availability of hybrid PET/CT and PET/MRI
                      scanners. Evaluation of the complex, multiparametric imaging
                      data can be achieved by methods from the emerging field of
                      artificial intelligence, potentially supporting physicians
                      in clinical routine. For example, time-consuming steps such
                      as manual detection and segmentation of lesions can be
                      performed fully automatically. Since computer-aided image
                      analysis is independent of the experience level of the
                      evaluating physician, the results are more standardized and
                      improve the inter-institutional comparability.},
      cin          = {INM-4 / INM-3},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-4-20090406 / I:(DE-Juel1)INM-3-20090406},
      pnm          = {5252 - Brain Dysfunction and Plasticity (POF4-525) / 5253 -
                      Neuroimaging (POF4-525) / DFG project 428090865 - Radiomics
                      basierend auf MRT und Aminosäure PET in der Neuroonkologie
                      (428090865)},
      pid          = {G:(DE-HGF)POF4-5252 / G:(DE-HGF)POF4-5253 /
                      G:(GEPRIS)428090865},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:33521635},
      UT           = {WOS:000897684800001},
      doi          = {10.1093/noajnl/vdaa179},
      url          = {https://juser.fz-juelich.de/record/890309},
}