data to support deid, best effort deidentify dicom with python and pydicom
Project description
Deidentify (deid) Data
Data for best effort anonymization for medical images in Python.
This data is supplementary to the Deid library and can be installed alongside it. It's required for tests and supplementary datasets, and you are free to use it for your own purposes! To install:
$ pip install deid-data
Please see our main Documentation.
Issues
If you have an issue with the data or want to request a new dataset, please do so on our issues board. For all other issues, please post to deid-issues
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
deid-data-0.0.20.tar.gz
(41.9 MB
view details)
File details
Details for the file deid-data-0.0.20.tar.gz.
File metadata
- Download URL: deid-data-0.0.20.tar.gz
- Upload date:
- Size: 41.9 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 33d455f13c82f76a39e8eb52d2808a35d7cde29c120819e246c863432281b8ed |
|
| MD5 | b9c318cd3a92e507ace7734415dbae5d |
|
| BLAKE2b-256 | 6330c4d9c1f1f0f7cb62445f0a82c1e6cf4e291e2ffdf976d3b1057a7e570daf |
