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DeepDefacer is a MRI anonymization tool written in Python, on top of Tensorflow and Keras, that was developed in partnership with the Poldrack Lab at Stanford University. It can be used to quickly deface 3D MRI images of any resolution and size on commercial CPUs and GPUs. Its goal is to provide the community with an easy to use and efficient tool for defacing medical images that require anonymization for compliance with federal privacy laws (e.g HIPAA).
If you use DeepDefacer in your work, please refer to this citation for the current version:
@article{khazane2019state,
title={DeepDefacer: Automatic Removal of Facial Features from MR Scans Via Deep Learning},
author={Anish Khazane, Julien Hoachuck, Dr. Chris Gorgowelski, Dr. Russell Poldrack},
journal={in proceedings, arXiv preprint},
year={2019}
}
If you use any of the architecture code from the ARFF-CNN, please also use the citation above to comply with its authors' instructions on referencing.
Deepdefacer can be easily installed on any operating system via Pypi. There are two versions of this package; CPU or GPU support. Please enter one of the following commands into your terminal window to begin installation, depending on your system specifications and desired python version.
CPU Support
pip install deepdefacer[tf_cpu] / pip3 install deepdefacer[tf_cpu]
GPU Support
pip install deepdefacer[tf_gpu] / pip3 install deepdefacer[tf_gpu]
Note: If you are using a ZSH-type shell, you may need to wrap the package name in quotations in order to successfully initiate the Pip installation. (e.g pip install "deepdefacer[...]"
).
Once installed, please enter deepdefacer --help
into your terminal window to see a list of available options for this program. Defacing a 3D MRI image is extremely simple, and can be done with the following command:
deepdefacer --input_file <input filename>
The program will output a defaced image in the same directory as the input file, unless --defaced_output_path
is specified.
You can also save the predicted mask for any MRI image by specifying the desired output filename and directory with the --mask_output_path
option.
FAQs
Automatic Removal of Facial Features from MRI Images
We found that deepdefacer 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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