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@ARTICLE{Truhn:982502,
      author       = {Truhn, Daniel and Tayebi Arasteh, Soroosh and Saldanha,
                      Oliver Lester and Müller-Franzes, Gustav and Khader, Firas
                      and Quirke, Philip and West, Nicholas P. and Gray, Richard
                      and Hutchins, Gordon G. A. and James, Jacqueline A. and
                      Loughrey, Maurice B. and Salto-Tellez, Manuel and Brenner,
                      Hermann and Brobeil, Alexander and Yuan, Tanwei and
                      Chang-Claude, Jenny and Hoffmeister, Michael and Foersch,
                      Sebastian and Han, Tianyu and Keil, Sebastian and
                      Schulze-Hagen, Maximilian and Isfort, Peter and Bruners,
                      Philipp and Kaissis, Georgios and Kuhl, Christiane and
                      Nebelung, Sven and Kather, Jakob Nikolas},
      title        = {{E}ncrypted federated learning for secure decentralized
                      collaboration in cancer image analysis},
      journal      = {Medical image analysis},
      volume       = {92},
      issn         = {1361-8423},
      reportid     = {RWTH-CONV-252585},
      pages        = {103059},
      year         = {2024},
      cin          = {532010-2 / 951320 / 811003-4 ; 924420},
      cid          = {$I:(DE-82)532010-2_20140620$ / $I:(DE-82)951320_20220218$ /
                      $I:(DE-82)811003-4_20140620$},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001138886700001},
      pubmed       = {pmid:38104402},
      doi          = {10.1016/j.media.2023.103059},
      url          = {https://publications.rwth-aachen.de/record/982502},
}