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@ARTICLE{Eke:1007217,
      author       = {Eke, Damian and Aasebø, Ida E. J. and Akintoye, Simisola
                      and Knight, William and Karakasidis, Alexandros and Mikulan,
                      Ezequiel and Ochang, Paschal and Ogoh, George and
                      Oostenveld, Robert and Pigorini, Andrea and Stahl, Bernd
                      Carsten and White, Tonya and Zehl, Lyuba},
      title        = {{P}seudonymisation of neuroimages and data protection:
                      {I}ncreasing access to data while retaining scientific
                      utility},
      journal      = {Neuroimage: reports},
      volume       = {1},
      number       = {4},
      issn         = {2666-9560},
      address      = {[Amsterdam]},
      publisher    = {Elsevier ScienceDirect},
      reportid     = {FZJ-2023-01989},
      pages        = {100053 -},
      year         = {2021},
      abstract     = {For a number of years, facial features removal techniques
                      such as ‘defacing’, ‘skull stripping’ and ‘face
                      masking/blurring’, were considered adequate privacy
                      preserving tools to openly share brain images.
                      Scientifically, these measures were already a compromise
                      between data protection requirements and research impact of
                      such data. Now, recent advances in machine learning and deep
                      learning that indicate an increased possibility of
                      re-identifiability from defaced neuroimages, have increased
                      the tension between open science and data protection
                      requirements. Researchers are left pondering how best to
                      comply with the different jurisdictional requirements of
                      anonymization, pseudonymisation or de-identification without
                      compromising the scientific utility of neuroimages even
                      further. In this paper, we present perspectives intended to
                      clarify the meaning and scope of these concepts and
                      highlight the privacy limitations of available
                      pseudonymisation and de-identification techniques. We also
                      discuss possible technical and organizational measures and
                      safeguards that can facilitate sharing of pseudonymised
                      neuroimages without causing further reductions to the
                      utility of the data.},
      cin          = {INM-1},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-1-20090406},
      pnm          = {5254 - Neuroscientific Data Analytics and AI (POF4-525) /
                      HBP SGA1 - Human Brain Project Specific Grant Agreement 1
                      (720270) / HBP SGA2 - Human Brain Project Specific Grant
                      Agreement 2 (785907) / HBP SGA3 - Human Brain Project
                      Specific Grant Agreement 3 (945539)},
      pid          = {G:(DE-HGF)POF4-5254 / G:(EU-Grant)720270 /
                      G:(EU-Grant)785907 / G:(EU-Grant)945539},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.1016/j.ynirp.2021.100053},
      url          = {https://juser.fz-juelich.de/record/1007217},
}