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Pseudonymisation of neuroimages and data protection: Increasing access to data while retaining scientific utility

Eke, Damian; Aasebø, Ida E.J.; Akintoye, Simisola; Knight, William; Karakasidis, Alexandros; Mikulan, Ezequiel; Ochang, Paschal; Ogoh, George; Oostenveld, Robert; Pigorini, Andrea; Stahl, Bernd Carsten; White, Tonya; Zehl, Lyuba

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Authors

DAMIAN EKE Damian.Eke@nottingham.ac.uk
Transitional Assistant Professor

Ida E.J. Aasebø

Simisola Akintoye

William Knight

Alexandros Karakasidis

Ezequiel Mikulan

Paschal Ochang

GEORGE OGOH George.Ogoh@nottingham.ac.uk
Senior Research Fellow

Robert Oostenveld

Andrea Pigorini

Tonya White

Lyuba Zehl



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 reidentifiability 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.

Journal Article Type Article
Acceptance Date Nov 25, 2021
Online Publication Date Sep 15, 2021
Publication Date 2021-12
Deposit Date Jan 17, 2024
Publicly Available Date Jan 18, 2024
Journal Neuroimage: Reports
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 1
Issue 4
Article Number 100053
DOI https://doi.org/10.1016/j.ynirp.2021.100053
Keywords Neuroimages, Anonymization, Pseudonymisation, Neurodata, de-identification, MRI, Data protection
Public URL https://nottingham-repository.worktribe.com/output/29835156
Publisher URL https://www.sciencedirect.com/science/article/pii/S2666956021000519?via%3Dihub

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