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Low-Effort Re-identification Techniques Based on Medical Imagery Threaten Patient Privacy

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Medical Image Understanding and Analysis (MIUA 2022)

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Abstract

Deriving patients’ identity from medical imagery threatens privacy, as these data are acquired to support diagnosis but not to reveal identity-related features. Still, for many medical imaging modalities, such identity breaches have been reported, however, typically employing a highly specialised image processing and pattern recognition pipeline. In this paper, we demonstrate that surprisingly, a simple and unified deep learning-based technique is able to determine patient identity from two exemplary imaging modalities, i.e., brain MRI and gastrointestinal endoscopic data. This demonstrates that almost anyone with limited resources and knowledge of the field would be able to perform this task, which indicates that according to GDPR, medical image data after pseudonymisation should be considered “information on an identifiable natural person” and thus must not be released to the public without further provisions.

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Notes

  1. 1.

    This figure has been designed using resources from [21].

  2. 2.

    This figure has been designed using resources from [19].

  3. 3.

    This figure has been designed using resources from [21].

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Authors and Affiliations

  1. Paris Lodron University of Salzburg, Salzburg, 5020, Austria

    Laura Carolina Martínez Esmeral & Andreas Uhl

Authors
  1. Laura Carolina Martínez Esmeral
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  2. Andreas Uhl
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Correspondence to Laura Carolina Martínez Esmeral .

Editor information

Editors and Affiliations

  1. Imperial College London, London, UK

    Guang Yang

  2. University of Cambridge, Cambridge, UK

    Angelica Aviles-Rivero

  3. University of Cambridge, Cambridge, UK

    Michael Roberts

  4. University of Cambridge, Cambridge, UK

    Carola-Bibiane Schönlieb

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Esmeral, L.C.M., Uhl, A. (2022). Low-Effort Re-identification Techniques Based on Medical Imagery Threaten Patient Privacy. In: Yang, G., Aviles-Rivero, A., Roberts, M., Schönlieb, CB. (eds) Medical Image Understanding and Analysis. MIUA 2022. Lecture Notes in Computer Science, vol 13413. Springer, Cham. https://doi.org/10.1007/978-3-031-12053-4_53

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  • DOI: https://doi.org/10.1007/978-3-031-12053-4_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-12052-7

  • Online ISBN: 978-3-031-12053-4

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