Abstract

Medical images are released with the reports that describe them, and protecting the image does not protect the report. This paper measures the text component of such releases. We measure identifier detection, downstream utility and residual identity leakage on the same documents, with the pseudonymisation policy as the variable under test: 15 detectors, three release conditions and four corpora of medical reports, legal judgments, news and other genres, and e-mail, in German, English, Chinese and Arabic. A fixed 13-detector union reaches a person sensitivity of 0.9998 at specificity 0.8686 on the medical reports, 0.9958 at 0.8504 on the legal judgments, 0.9352 at 0.9318 on news and other genres, and 0.9906 at 0.6235 on e-mail. With this ensemble, frequency matching with a public name list recovers zero identities by alignment across the four corpora; the names it got right were ones the detector missed, left in clear text. Cross-document linkage ranks the correct person first for 0.93% of e-mail queries without training and 3.94% with it, against 1/3697 chance and 71.98% on unmodified text. On the medical reports it recovers nothing without training and 0.71% of 138 queries with it, against 1/207 chance and a 2.73% ceiling on unmodified text.

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Open access
Green open access

Cite this article

APA 7

Maier, A., Hinrichs-Mayer, M., Weber, F., Lackner, N., May, M., Kainz, B., & Bayer, S. (2026). The Text Beside the Image: Detection, Utility and Leakage for Trustworthy Multimodal Medical Data and Beyond. https://omanscience.com/en/articles/the-text-beside-the-image-detection-utility-and-leakage-for-trustworthy-multimodal-medical-data-and-beyond

MLA 9

Maier, Andreas, et al. "The Text Beside the Image: Detection, Utility and Leakage for Trustworthy Multimodal Medical Data and Beyond." https://omanscience.com/en/articles/the-text-beside-the-image-detection-utility-and-leakage-for-trustworthy-multimodal-medical-data-and-beyond.

Chicago (author–date)

Maier, Andreas, Monica Hinrichs-Mayer, Franziska Weber, Niklas Lackner, Matthias May, Bernhard Kainz, and Siming Bayer. 2026. "The Text Beside the Image: Detection, Utility and Leakage for Trustworthy Multimodal Medical Data and Beyond." https://omanscience.com/en/articles/the-text-beside-the-image-detection-utility-and-leakage-for-trustworthy-multimodal-medical-data-and-beyond.

Harvard

Maier, A., Hinrichs-Mayer, M., Weber, F., Lackner, N., May, M., Kainz, B. and Bayer, S. (2026) 'The Text Beside the Image: Detection, Utility and Leakage for Trustworthy Multimodal Medical Data and Beyond', Available at: https://omanscience.com/en/articles/the-text-beside-the-image-detection-utility-and-leakage-for-trustworthy-multimodal-medical-data-and-beyond.

Vancouver

Maier A, Hinrichs-Mayer M, Weber F, Lackner N, May M, Kainz B, et al. The Text Beside the Image: Detection, Utility and Leakage for Trustworthy Multimodal Medical Data and Beyond. https://omanscience.com/en/articles/the-text-beside-the-image-detection-utility-and-leakage-for-trustworthy-multimodal-medical-data-and-beyond

IEEE

A. Maier, M. Hinrichs-Mayer, F. Weber, N. Lackner, M. May, B. Kainz, and S. Bayer, "The Text Beside the Image: Detection, Utility and Leakage for Trustworthy Multimodal Medical Data and Beyond," https://omanscience.com/en/articles/the-text-beside-the-image-detection-utility-and-leakage-for-trustworthy-multimodal-medical-data-and-beyond.