dicognito 0.15.0

A tool for anonymizing DICOM files

Dicognito is a Python module and command-line utility that anonymizes DICOM files.

Use it to anonymize one or more DICOM files belonging to one or any number of patients. Objects will remain grouped in their original patients, studies, and series.

Anonymization causes significant attributes, such as identifiers, names, and addresses, to be replaced by new values. Dates and times will be shifted into the past, but their order will remain consistent within and across the files.

The package is available on pypi and can be installed from the command line by typing

pip install dicognito

Anonymizing from the command line

Once installed, a dicognito command will be added to your Python scripts directory. You can run it on entire filesystem trees or a collection of files specified by glob like so:

# Recurse down the filesystem, anonymizing all found DICOM files.
# Anonymized files will be placed in out-dir, named by new SOP
# instance UID.
dicognito --output-directory out-dir .

# Anonymize all files in the current directory with the dcm extension
# (-o is an alias for --output-directory).
dicognito -o out-dir *.dcm

# Anonymize all files in the current directory with the dcm extension
# but overwrite the original files.
# Note: repeatedly anonymizing the same files will cause date attributes
# to  move farther into the past.
dicognito --in-place *.dcm

Get more help via dicognito --help.

Anonymizing from within Python

To anonymize a bunch of DICOM objects from within a Python program, import the objects using pydicom and use the Anonymizer class:

import pydicom
import dicognito.anonymizer

anonymizer = dicognito.anonymizer.Anonymizer()

for original_filename in ("original1.dcm", "original2.dcm"):
    with pydicom.dcmread(original_filename) as dataset:
        anonymizer.anonymize(dataset)
        dataset.save_as("clean-" + original_filename)

Use a single Anonymizer on datasets that might be part of the same series, or the identifiers will not be consistent across objects.

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Logo: Remixed from Radiology by priyanka and Incognito by d͡ʒɛrmi Good from the Noun Project.