Multisite Comparison of MRI Defacing Software Across Multiple Cohorts.

ABSTRACT: With improvements to both scan quality and facial recognition software, there is an increased risk of participants being identified by a 3D render of their structural neuroimaging scans, even when all other personal information has been removed. To prevent this, facial features should be removed before data are shared or openly released, but while there are several publicly available software algorithms to do this, there has been no comprehensive review of their accuracy within the general population. To address this, we tested multiple algorithms on 300 scans from three neuroscience research projects, funded in part by the Ontario Brain Institute, to cover a wide range of ages (3-85 years) and multiple patient cohorts. While skull stripping is more thorough at removing identifiable featur

SUBMITTER: Theyers AE 

PROVIDER: S-EPMC7943842 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature