Outputs of BIDSonym¶
BIDSonym generates three broad classes of outcomes:
Visual QA (quality assessment): one graphic showing the overlay between the outcome of brain extraction and defaced images per image and one gif per defaced image per subject, that allows the user a visual assessment of the quality of de-identification and ensures the transparency of
BIDSonym
’s operation.imaging data including defaced images in the BIDS root directory and non-defaced images in the sourcedata/bidsonym directory.
sidecar JSON and metadata .tsv files including de-identified files in the BIDS root directory and not de-identified files in the sourcedata/bidsonym directory.
Visual QA¶
BIDSonym
related graphical outputs, written to sourcedata/bidsonym/sub-<subject_label>/(ses-<session_label>)
.
These graphics provide a quick way to make a visual inspection of the de-identification easy.
Within static graphics, each displays the whole defaced image
in 10 slices along different
directions (x,y,z). To evaluate if the defacing
was too stringent, a brainmask
created before
the defacing
is overlaid. The graphics additionally include a gif within which the defaced image
is scrolled
through each direction.
Imaging data¶
Regarding Imaging data
two types of outputs will be created when running BIDSonym
:
copied non-defaced images¶
The non-defaced images that enter BIDSonym
as input will be copied
to sourcedata/bidsonym/sub-<subject_label>/
and provide with a no_deid
identifier in their filename. For example:
bids_dataset/sub-<subject_label>/anat/sub-<subject_label>_T1w.nii.gz
will be copied and renamed to
bids_dataset/sourcedata/bidsonym/sub-<subject_label>/sub-<subject_label>_T1w_no_deid.nii.gz
.
This step is intended to keep the non-defaced images
in case the defacing did not succeed (for
example too much or too little information cut out), so that users can copy the non-defaced images
back to the bids_dataset
directory and do not need to convert the non-defaced images from DICOM
again.
and
defaced images¶
The images of either a specified participant or the whole group (depending on the analysis_level parameter
, please see Usage)
in the bids_dataset
will be defaced via the specified defacing algorithm (please see Usage).
Neither the data structure nor the filenames will be changed. For example:
bids_dataset/sub-<subject_label>/anat/sub-<subject_label>_T1w.nii.gz
will be defaced, overwriting
the input image, so that the bids_dataset
directory contains only de-identified data which then
can be entered into a processing pipeline and/or publicly shared (once again, depending on the regulations
of the country you’re in and/or acquired the data in).
Sidecar JSON and metadata .tsv files¶
Regarding Sidecar JSON and metadata .tsv files
three types of outputs will be created when running BIDSonym
:
metadata .tsv files¶
BIDSonym
will access both the information stored in the header
of the images and sidecar JSON files
, writing them
to .tsv
files with two columns: 1. the type of information and 2. if it might be problematic in terms of data sharing. By default,
the descrip
field is considered to be problematic in the header
and the following in the sidecar JSON files
: AcquisitionTime
,
InstitutionAddress
, InstitutionName
, InstitutionalDepartmentName
, ProcedureStepDescription
, ProtocolName
,
PulseSequenceDetails
, SeriesDescription
and global
. However, the user can provide a list of strings for which will be
searched in the extracted information via the --check_meta_data
argument. For the defaults and if a certain string, e.g., name
or location
is found, the
respective field is marked as maybe
in the problematic
column. Thus users can investigate and evaluate if potentially
sensitive information is present in the data and, if not done already, indicate metadata fields which information should be
deleted through the --del_meta
argument. However, only metadata from the sidecar JSON files
but not the image headers
will be deleted.
copied non-de-identified sidecar JSON files¶
Comparable to the non-defaced images
, the non-de-identified
sidecar JSON files
will be copied to sourcedata/bidsonym/sub-<subject_label>/
and provided with a no-deid
identifier. Here’s an example:
bids_dataset/sub-<subject_label>/anat/sub-<subject_label>_T1w.json
will be copied and renamed to
bids_dataset/sourcedata/sub-<subject_label>/anat/sub-<subject_label>_T1w_no_deid.json
.
This step is intended to keep the non-de-identified
sidecar JSON files
in case the de-identification did not succeed , so that users can copy
the non-de-identified sidecar JSON files
back to the bids_dataset
directory and do not need to do run the conversion again.
Please not that while de-facing only targets structural data
, the sidecar JSON files
of all modalities will be included.
de-identified sidecar JSON files¶
If set by the user through the --del_meta
argument, BIDSonym
will deleted
the value of indicated metadata fields
in the sidecar JSON files
within the
bids_dataset
directory, replacing them with the string deleted_by_bidsonym
.
For example, if the metadata field
InstitutionAddress
should be deleted,
the respective value of the sidecar JSON files
will change from e.g.,
InstitutionAddress : 'A restaurant at the end of the Universe.'
to
InstitutionAddress : 'deleted_by_bidsonym'
.