deidentify dicom and other images with python and pydicom
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
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|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size deid-0.1.34-py3.7.egg (5.0 MB)||File type Egg||Python version 3.7||Upload date||Hashes View hashes|
|Filename, size deid-0.1.34-py3-none-any.whl (5.0 MB)||File type Wheel||Python version py3||Upload date||Hashes View hashes|
|Filename, size deid-0.1.34.tar.gz (5.0 MB)||File type Source||Python version None||Upload date||Hashes View hashes|