Skip to main content

Automatic Removal of Facial Features from MRI Images

Project description

DeepDefacer: Automatic Removal of Facial Features via Deep Learning.

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).

Referencing and citing DeepDefacer

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.

Requirements

  • Any Python version between 2.7 and 3.6.
  • If you are using the GPU version of this library, please ensure that your GPU drivers are correctly installed and up to date. Please reference GPU Support for Tensorflow-GPU for further details on GPU setup.
  • Input MRI images must have 3D structure and be saved in either .nii or .nii.gz format.

Installation

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[...]").

Usage and Documentation

Once installed, please enter deepdefacer --help into your terminal window to see a list of available tools within this program. Defacing a 3D MRI image is extremely simple, and can be done with the following command:

deepdefacer <input filename>

The program will output a defaced image in the same directory as the input file.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

deepdefacer-2.0.9.tar.gz (5.3 MB view details)

Uploaded Source

File details

Details for the file deepdefacer-2.0.9.tar.gz.

File metadata

  • Download URL: deepdefacer-2.0.9.tar.gz
  • Upload date:
  • Size: 5.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.8.0 tqdm/4.29.1 CPython/2.7.10

File hashes

Hashes for deepdefacer-2.0.9.tar.gz
Algorithm Hash digest
SHA256 a06557817c602aaed850039b4f21be49960fe7ccc822e1e71a0d623fbe5299f4
MD5 0827e4640d1af9f14bc8d3d8e2148bdf
BLAKE2b-256 f6372302aa5d9684107f7f71be303ceb0bcccc4ea2a11f12b08a2dfa53311af6

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page