Re-identification of anonymised MRI head images with publicly available software: investigation of the current risk to patient privacy.

ABSTRACT:

Background

Facial recognition software (FRS) has historically been perceived as lacking the capability to identify individuals from cross-sectional medical images. Utilising such data for identification purposes was considered infeasible due to the substantial computational power and specialised technical expertise it would require. However, recent advancements in accessible artificial intelligence-based (AI-based) software and open-source tools have made these applications widely available and easy to use, raising new privacy concerns.

Methods

This proof-of-concept was designed as a cross-sectional study and included participants with a verified online presence. Standard magnetic resonance imaging (MRI) head scans were performed on these participants, from which three-dimen

SUBMITTER: Steeg K 

PROVIDER: S-EPMC11617779 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature