best effort deidentify dicom with python and pydicom

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  • License: MIT License (LICENSE)
  • Author: Vanessa Sochat
  • Tags open source, python, anonymize, dicom
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Project description

Deidentify (deid)

Best effort anonymization for medical images in Python.

DOI Build Status

Please see our Documentation.

These are basic Python based tools for working with medical images and text, specifically for de-identification. The cleaning method used here mirrors the one by CTP in that we can identify images based on known locations. We are looking for collaborators to develop and validate an OCR cleaning method! Please reach out if you would like to help work on this.

Installation

Local

For the stable release, install via pip:

pip install deid

For the development version, install from Github:

pip install git+git://github.com/pydicom/deid

Docker

docker build -t pydicom/deid .
docker run pydicom/deid --help

Issues

If you have an issue, or want to request a feature, please do so on our issues board.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for vsochat from gravatar.com vsochat

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (LICENSE)
  • Author: Vanessa Sochat
  • Tags open source, python, anonymize, dicom
Classifiers

Release history Release notifications | RSS feed

0.3.25

0.3.24

0.3.23

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0.3.21

0.3.2

0.3.0

0.2.37

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0.2.34

0.2.33

This version

0.2.32

0.2.31

0.2.29

0.2.28

0.2.27

0.2.26

0.2.25

0.2.24

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0.0.1

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