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@ARTICLE{Quarz:353135,
      author       = {Quarz, Anastasiia and Volz, Lennart and Antink, C Hoog and
                      Durante, Marco and Graeff, Christian},
      title        = {{D}eep learning-based voxel sampling for particle therapy
                      treatment planning},
      journal      = {Physics in medicine and biology},
      volume       = {69},
      number       = {15},
      issn         = {0031-9155},
      address      = {Bristol},
      publisher    = {IOP Publ.},
      reportid     = {GSI-2024-00800},
      pages        = {155014},
      year         = {2024},
      note         = {Original content from this work may be used under the terms
                      of the Creative Commons Attribution 4.0 license.},
      keywords     = {Deep Learning / Radiotherapy Planning, Computer-Assisted:
                      methods / Humans / Heavy Ion Radiotherapy: methods / Head
                      and Neck Neoplasms: radiotherapy / Head and Neck Neoplasms:
                      diagnostic imaging / Organs at Risk: radiation effects /
                      deep-learning (Other) / optimization (Other) / particle
                      therapy (Other) / treatment planning (Other)},
      cin          = {BIO / BIO@FAIR},
      ddc          = {530},
      cid          = {I:(DE-Ds200)BIO-20160831OR354 / I:(DE-Ds200)Coll-FAIR-BIO},
      pnm          = {633 - Life Sciences – Building Blocks of Life: Structure
                      and Function (POF4-633) / SUC-GSI-Darmstadt - Strategic
                      university cooperation GSI-TU Darmstadt (SUC-GSI-DA) /
                      HITRIplus - Heavy Ion Therapy Research Integration plus
                      (101008548)},
      pid          = {G:(DE-HGF)POF4-633 / G:(DE-Ds200)SUC-GSI-DA /
                      G:(EU-Grant)101008548},
      experiment   = {$EXP:(DE-Ds200)no_experiment-20200803$},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:38917844},
      UT           = {WOS:001272880200001},
      doi          = {10.1088/1361-6560/ad5bba},
      url          = {https://repository.gsi.de/record/353135},
}