mede 0.0.2

De-Identification of Medical Imaging Data: A Comprehensive Tool for Ensuring Patient Privacy

De-Identification of Medical Imaging Data: A Comprehensive Tool for Ensuring Patient Privacy

Getting started • Usage • Citation

[!IMPORTANT]
The package is now available on PyPI: pip install mede

This repository contains the De-Identification of Medical Imaging Data: A Comprehensive Tool for Ensuring Patient Privacy, which enables the user to anonymize a wide variety of medical imaging types, including Magnetic Resonance Imaging (MRI), Computer Tomography (CT), Ultrasound (US), Whole Slide Images (WSI) or MRI raw data (twix).

This tool combines multiple anonymization steps, including metadata deidentification, defacing and skull-stripping while being faster than current state-of-the-art deidentification tools.

Getting started

You can install the anonymization tool directly via pip (recommended) or via Docker.

Installation via pip

Our tool is available via pip. You can install it with the following command:

pip install mede

Additional dependencies for text removal

If you want to use the text removal feature, you also need to install Google's Tesseract OCR engine. You can find the installation instructions for your operating system here. On Ubuntu, you can install it via

sudo apt install tesseract-ocr
sudo apt install libtesseract-dev

On MacOS, you can install it via Homebrew:

brew install tesseract

Installation via Docker

Alternatively this tool is distributed via docker. You can find the docker images here. The docker image is available for amd64 and arm64 platforms.

For the installation and execution of the docker image, you must have Docker installed on your system.

1. Pull the docker image

   docker pull morrempe/hold:[tag]   (either arm64 or amd64)
   

2. Run the docker container with attached volume. Your data will be mounted in the data folder:

   docker run --rm -it -v [Path/to/your/data]:/data morrempe/hold:[tag]
   

3. Run the script with the corresponding cli parameter, e.g.:

   python3 deidentify.py [your flags]
   

Usage

De-Identification CLI

usage: mede-deidentify [-h] [-v | --verbose | --no-verbose] [-t | --text-removal | --no-text-removal] [-i INPUT]
                                    [-o OUTPUT] [--gpu GPU] [-s | --skull_strip | --no-skull_strip] [-de | --deface | --no-deface]
                                    [-tw | --twix | --no-twix] [-p PROCESSES]
                                    [-d {basicProfile,cleanDescOpt,cleanGraphOpt,cleanStructContOpt,rtnDevIdOpt,rtnInstIdOpt,rtnLongFullDatesOpt,rtnLongModifDatesOpt,rtnPatCharsOpt,rtnSafePrivOpt,rtnUIDsOpt} [{basicProfile,cleanDescOpt,cleanGraphOpt,cleanStructContOpt,rtnDevIdOpt,rtnInstIdOpt,rtnLongFullDatesOpt,rtnLongModifDatesOpt,rtnPatCharsOpt,rtnSafePrivOpt,rtnUIDsOpt} ...]]

options:
  -h, --help            show this help message and exit
  -v, --verbose, --no-verbose
  -t, --text-removal, --no-text-removal
  -i INPUT, --input INPUT
                        Path to the input data.
  -o OUTPUT, --output OUTPUT
                        Path to save the output data.
  --gpu GPU             GPU device number. (default 0)
  -s, --skull_strip, --no-skull_strip
  -de, --deface, --no-deface
  -tw, --twix, --no-twix
  -w, --wsi, --no-wsi
  -p PROCESSES, --processes PROCESSES
                        Number of processes to use for multiprocessing.
  -d {basicProfile,cleanDescOpt,cleanGraphOpt,cleanStructContOpt,rtnDevIdOpt,rtnInstIdOpt,rtnLongFullDatesOpt,rtnLongModifDatesOpt,rtnPatCharsOpt,rtnSafePrivOpt,rtnUIDsOpt} [{basicProfile,cleanDescOpt,cleanGraphOpt,cleanStructContOpt,rtnDevIdOpt,rtnInstIdOpt,rtnLongFullDatesOpt,rtnLongModifDatesOpt,rtnPatCharsOpt,rtnSafePrivOpt,rtnUIDsOpt} ...], --deidentification-profile {basicProfile,cleanDescOpt,cleanGraphOpt,cleanStructContOpt,rtnDevIdOpt,rtnInstIdOpt,rtnLongFullDatesOpt,rtnLongModifDatesOpt,rtnPatCharsOpt,rtnSafePrivOpt,rtnUIDsOpt} [{basicProfile,cleanDescOpt,cleanGraphOpt,cleanStructContOpt,rtnDevIdOpt,rtnInstIdOpt,rtnLongFullDatesOpt,rtnLongModifDatesOpt,rtnPatCharsOpt,rtnSafePrivOpt,rtnUIDsOpt} ...]
                        Which DICOM deidentification profile(s) to apply. (default None)

Citation

If you use our tool in your work, please cite us with the following BibTeX entry.

@article{rempe2025identification,
  title={De-identification of medical imaging data: a comprehensive tool for ensuring patient privacy},
  author={Rempe, Moritz and Heine, Lukas and Seibold, Constantin and H{\"o}rst, Fabian and Kleesiek, Jens},
  journal={European Radiology},
  pages={1--10},
  year={2025},
  publisher={Springer}
}