Skip to main content

A tool for anonymizing DICOM files

Project description

Dicognito logo

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.

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:

dicognito .      # recurses down the filesystem, anonymizing all found DICOM files
dicognito *.dcm  # anonymizes all files in the current directory with the dcm extension

Files will be anonymized in place, with significant attributes, such as identifiers, names, and addresses, replaced by random values. Dates and times will be shifted a random amount, but their order will remain consistent within and across the files.

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:
        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.

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

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dicognito-0.13.0.tar.gz (30.5 kB view hashes)

Uploaded source

Built Distribution

dicognito-0.13.0-py3-none-any.whl (33.9 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page