OpenfMRI has been deprecated. For new and up to date datasets please use

Old dataset pages are available at

Information on De-identification of fMRI Data

To protect the privacy of the individuals who have been scanned we require that all subjects be de-identified before publishing a dataset. For the purposes of fMRI de-facing is the preferred method de-identification of scan data. Skull stripped data will not be accepted for publication.

Two tools we recommend to de-face images with are pydeface and mri_deface. Examples of de-facing are shown below. Left is the original image, middle has been processed by pydeface, and the right by mri_deface:



mri_deface can be found here and is offered as binaries. The mri_deface web site has instructions for its use as well as the template files available. . For OS X users note that your browser may de-compress certain files as you download them so the unzip step for the binary may be unnecessary.

Pydeface can be found here and is implemented in python. It requires FSL to be installed in order to work and it ships with its own template and facemask.

In addition to de-facing the high resolution images, please make sure that any potential identifying elements are removed from text files and image headers. One potential tool for this is  DeID. It is written in java and has a graphical user interface. Note thatthere are currently some issues with running in OS X: