Removing facial features from structural MRI images biases visual quality assessment.

ABSTRACT: A critical step before data-sharing of human neuroimaging is removing facial features to protect individuals' privacy. However, not only does this process redact identifiable information about individuals, but it also removes non-identifiable information. This introduces undesired variability into downstream analysis and interpretation. This registered report investigated the degree to which the so-called defacing altered the quality assessment of T1-weighted images of the human brain from the openly available "IXI dataset". The effect of defacing on manual quality assessment was investigated on a single-site subset of the dataset (N = 185). By comparing two linear mixed-effects models, we determined that four trained human raters' perception of quality was significantly influenced by defa

SUBMITTER: Provins C 

PROVIDER: S-EPMC12143891 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature