Privacy risks of whole-slide image sharing in digital pathology

J 2023

Privacy risks of whole-slide image sharing in digital pathology

HOLUB, Petr, Heimo MÜLLER, Tomáš BÍL, Luca PIREDDU, Markus PLASS et. al.

Základní údaje

Originální název

Privacy risks of whole-slide image sharing in digital pathology

Autoři

HOLUB, Petr (203 Česká republika, garant, domácí), Heimo MÜLLER, Tomáš BÍL (203 Česká republika, domácí), Luca PIREDDU, Markus PLASS, Fabian PRASSER, Irene SCHLÜNDER, Kurt ZATLOUKAL, Rudolf NENUTIL (203 Česká republika) a Tomáš BRÁZDIL (203 Česká republika, domácí)

Vydání

Nature Communications, 2023, 2041-1723

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Německo

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 16.600 v roce 2022

Kód RIV

RIV/00216224:14610/23:00130727

Organizační jednotka

Ústav výpočetní techniky

DOI

http://dx.doi.org/10.1038/s41467-023-37991-y

UT WoS

001001562200003

Klíčová slova anglicky

digital pathology; whole slide images; anonymity; privacy risks; data sharing

Změněno: 5. 4. 2024 11:00, Mgr. Alena Mokrá

Anotace

V originále

Access to large volumes of so-called whole-slide images—high-resolution scans of complete pathological slides—has become a cornerstone of the development of novel artificial intelligence methods in pathology for diagnostic use, education/training of pathologists, and research. Nevertheless, a methodology based on risk analysis for evaluating the privacy risks associated with sharing such imaging data and applying the principle “as open as possible and as closed as necessary” is still lacking. In this article, we develop a model for privacy risk analysis for whole-slide images which focuses primarily on identity disclosure attacks, as these are the most important from a regulatory perspective. We introduce a taxonomy of whole-slide images with respect to privacy risks and mathematical model for risk assessment and design . Based on this risk assessment model and the taxonomy, we conduct a series of experiments to demonstrate the risks using real-world imaging data. Finally, we develop guidelines for risk assessment and recommendations for low-risk sharing of whole-slide image data.

Návaznosti

90125, velká výzkumná infrastruktura

Název: BBMRI-CZ III

Citovat

HOLUB, Petr, Heimo MÜLLER, Tomáš BÍL, Luca PIREDDU, Markus PLASS, Fabian PRASSER, Irene SCHLÜNDER, Kurt ZATLOUKAL, Rudolf NENUTIL a Tomáš BRÁZDIL. Privacy risks of whole-slide image sharing in digital pathology. Nature Communications. 2023, roč. 14, č. 2577, s. 1-15. ISSN 2041-1723. Dostupné z: https://dx.doi.org/10.1038/s41467-023-37991-y.

@article{2280138,
   author = {Holub, Petr and Müller, Heimo and Bíl, Tomáš and Pireddu, Luca and Plass, Markus and Prasser, Fabian and Schlünder, Irene and Zatloukal, Kurt and Nenutil, Rudolf and Brázdil, Tomáš},
   article_number = {2577},
   doi = {http://dx.doi.org/10.1038/s41467-023-37991-y},
   keywords = {digital pathology; whole slide images; anonymity; privacy risks; data sharing},
   language = {eng},
   issn = {2041-1723},
   journal = {Nature Communications},
   title = {Privacy risks of whole-slide image sharing in digital pathology},
   url = {https://www.nature.com/articles/s41467-023-37991-y},
   volume = {14},
   year = {2023}
}

TY  - JOUR
ID  - 2280138
AU  - Holub, Petr - Müller, Heimo - Bíl, Tomáš - Pireddu, Luca - Plass, Markus - Prasser, Fabian - Schlünder, Irene - Zatloukal, Kurt - Nenutil, Rudolf - Brázdil, Tomáš
PY  - 2023
TI  - Privacy risks of whole-slide image sharing in digital pathology
JF  - Nature Communications
VL  - 14
IS  - 2577
SP  - 1-15
EP  - 1-15
SN  - 20411723
KW  - digital pathology
KW  - whole slide images
KW  - anonymity
KW  - privacy risks
KW  - data sharing
UR  - https://www.nature.com/articles/s41467-023-37991-y
N2  - Access to large volumes of so-called whole-slide images—high-resolution scans of complete pathological slides—has become a cornerstone of the development of novel artificial intelligence methods in pathology for diagnostic use, education/training of pathologists, and research. Nevertheless, a methodology based on risk analysis for evaluating the privacy risks associated with sharing such imaging data and applying the principle “as open as possible and as closed as necessary” is still lacking. In this article, we develop a model for privacy risk analysis for whole-slide images which focuses primarily on identity disclosure attacks, as these are the most important from a regulatory perspective. We introduce a taxonomy of whole-slide images with respect to privacy risks and mathematical model for risk assessment and design . Based on this risk assessment model and the taxonomy, we conduct a series of experiments to demonstrate the risks using real-world imaging data. Finally, we develop guidelines for risk assessment and recommendations for low-risk sharing of whole-slide image data.
ER  -

HOLUB, Petr, Heimo MÜLLER, Tomáš BÍL, Luca PIREDDU, Markus PLASS, Fabian PRASSER, Irene SCHLÜNDER, Kurt ZATLOUKAL, Rudolf NENUTIL a Tomáš BRÁZDIL. Privacy risks of whole-slide image sharing in digital pathology. \textit{Nature Communications}. 2023, roč.~14, č.~2577, s.~1-15. ISSN~2041-1723. Dostupné z: https://dx.doi.org/10.1038/s41467-023-37991-y.

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