Metadata-Version: 2.1
Name: dicognito
Version: 0.5.0
Summary: A tool for anonymizing DICOM files
Home-page: https://github.com/blairconrad/dicognito
Author: Blair Conrad
Author-email: blair@blairconrad.com
License: MIT
Download-URL: https://github.com/blairconrad/dicognito/archive/0.5.0.tar.gz
Description: ![Dicognito logo](https://github.com/blairconrad/dicognito/raw/master/assets/dicognito_128.png "Dicognito logo")
        
        Dicognito is a [Python](https://www.python.org/) module and command-line utility that anonymizes
        [DICOM](https://www.dicomstandard.org/) 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](https://pypi.org/project/dicognito/) 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 you Python scripts directory. You can run it on a collection
        of files specified by glob like so:
        
        ```
        dicognito *.dcm
        ```
        
        Anonymized versions of the files will be created, 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.
        
        The new files will all be named "anon-_original filename_" and will appear next to the original ones.
        
        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](https://pydicom.github.io/) and use the `Anonymizer` class:
        
        ```python
        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.
        
        ----
        Logo: Remixed from [Radiology](https://thenounproject.com/search/?q=x-ray&i=1777366)
        by [priyanka](https://thenounproject.com/creativepriyanka/) and [Incognito](https://thenounproject.com/search/?q=incognito&i=7572) by [d͡ʒɛrmi Good](https://thenounproject.com/geremygood/) from [the Noun Project](https://thenounproject.com/).
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Healthcare Industry
Description-Content-Type: text/markdown
