UCSF

INTRODUCTION: Recent technological advances have increased the risk that de-identified brain images could be re-identified from face imagery. The Alzheimers Disease Neuroimaging Initiative (ADNI) is a leading source of publicly available de-identified brain imaging, who quickly acted to protect participants privacy. METHODS: An independent expert committee evaluated 11 face-deidentification (de-facing) methods and selected four for formal testing. RESULTS: Effects of de-facing on brain measurements were comparable across methods and sufficiently small to recommend de-facing in ADNI. The committee ultimately recommended mri_reface for advantages in reliability, and for some practical considerations. ADNI leadership approved the committees recommendation, beginning in ADNI4. DISCUSSION: ADNI4 de-faces all applicable brain images before subsequent pre-processing, analyses, and public release. Trained analysts inspect de-faced images to confirm complete face removal and complete non-modification of brain. This paper details the history of the algorithm selection process and extensive validation, then describes the production workflows for de-facing in ADNI. HIGHLIGHTS: ADNI is implementing de-facing of MRI and PET beginning in ADNI4. De-facing alters face imagery in brain images to help protect privacy. Four algorithms were extensively compared for ADNI and mri_reface was chosen. Validation confirms mri_reface is robust and effective for ADNI sequences. Validation confirms mri_reface negligibly affects ADNI brain measurements.