# Conditional De-Identification of 3D Magnetic Resonance Images

Source: [Conditional De-Identification of 3D Magnetic Resonance Images](<https://www.sota2.com/research/paper/68fa6b0c1e209131cea2bb43>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T23:38:16.503Z

Authors: Lennart Alexander Van der Goten, Tobias Hepp, Zeynep Akata, Kevin Smith

Published: 2021-10-18T15:19:35.000Z

## Abstract

Privacy protection of medical image data is challenging. Even if metadata is removed, brain scans are vulnerable to attacks that match renderings of the face to facial image databases. Solutions have been developed to de-identify diagnostic scans by obfuscating or removing parts of the face. However, these solutions either fail to reliably hide the patient's identity or are so aggressive that they impair further analyses. We propose a new class of de-identification techniques that, instead of removing facial features, remodels them. Our solution relies on a conditional multi-scale GAN architecture. It takes a patient's MRI scan as input and generates a 3D volume conditioned on the patient's brain, which is preserved exactly, but where the face has been de-identified through remodeling. We demonstrate that our approach preserves privacy far better than existing techniques, without compromising downstream medical analyses. Analyses were run on the OASIS-3 and ADNI corpora.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [User-based De-identification Matching on OASIS-3](<https://www.sota2.com/research/sota/user-based-de-identification-matching-on-oasis-3.md>): User-based De-identification Matching; OASIS-3; Accuracy: 30.47.

- [User-based De-identification Matching on ADNI](<https://www.sota2.com/research/sota/user-based-de-identification-matching-on-adni.md>): User-based De-identification Matching; ADNI; Accuracy: 56.11.

- [Model-based De-identification Matching on OASIS-3](<https://www.sota2.com/research/sota/model-based-de-identification-matching-on-oasis-3.md>): Model-based De-identification Matching; OASIS-3; Accuracy: 56.4.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2110.09927>)

[PDF](<https://arxiv.org/pdf/2110.09927.pdf>)