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        "author": "Blair Conrad",
        "author_email": "blair@blairconrad.com",
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            "Development Status :: 3 - Alpha",
            "Environment :: Console",
            "Intended Audience :: Healthcare Industry",
            "License :: OSI Approved :: MIT License",
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            "Programming Language :: Python :: 3.7"
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        "description": "![Dicognito logo](https://github.com/blairconrad/dicognito/raw/master/assets/dicognito_128.png \"Dicognito logo\")\n\nDicognito is a [Python](https://www.python.org/) module and command-line utility that anonymizes\n[DICOM](https://www.dicomstandard.org/) files.\n\nUse it to anonymize one or more DICOM files belonging to one or any number of patients. Objects will remain grouped\nin their original patients, studies, and series.\n\nThe package is [available on pypi](https://pypi.org/project/dicognito/) and can be installed from the command line by typing\n\n```\npip install dicognito\n```\n\n## Anonymizing from the command line\n\nOnce installed, a `dicognito` command will be added to your Python scripts directory.\nYou can run it on entire filesystem trees or a collection of files specified by glob like so:\n\n```\ndicognito .      # recurses down the filesystem, anonymizing all found DICOM files\ndicognito *.dcm  # anonymizes all files in the current directory with the dcm extension\n```\n\nFiles will be anonymized in place, with significant attributes, such as identifiers, names, and\naddresses, replaced by random values. Dates and times will be shifted a random amount, but their\norder will remain consistent within and across the files.\n\nGet more help via `dicognito --help`.\n\n## Anonymizing from within Python\n\nTo anonymize a bunch of DICOM objects from within a Python program, import the objects using\n[pydicom](https://pydicom.github.io/) and use the `Anonymizer` class:\n\n```python\nimport pydicom\nimport dicognito.anonymizer\n\nanonymizer = dicognito.anonymizer.Anonymizer()\n\nfor original_filename in (\"original1.dcm\", \"original2.dcm\"):\n    with pydicom.dcmread(original_filename) as dataset:\n        anonymizer.anonymize(dataset)\n        dataset.save_as(\"clean-\" + original_filename)\n```\n\nUse a single `Anonymizer` on datasets that might be part of the same series, or the identifiers will not be\nconsistent across objects.\n\n----\nLogo: Remixed from [Radiology](https://thenounproject.com/search/?q=x-ray&i=1777366)\nby [priyanka](https://thenounproject.com/creativepriyanka/) and [Incognito](https://thenounproject.com/search/?q=incognito&i=7572) by [d\u00cd\u00a1\u00ca\u2019\u00c9\u203armi Good](https://thenounproject.com/geremygood/) from [the Noun Project](https://thenounproject.com/).\n\n\n",
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