Best effort anonymization for medical images in Python.
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.
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 build -t pydicom/deid .
docker run pydicom/deid --help
If you have an issue, or want to request a feature, please do so on our issues board.
FAQs
best effort deidentify dicom with python and pydicom
We found that deid demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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