https://github.com/adgaudio/deepfixcx

DeepFix: Explainable Privacy-Preserving Image Compression for Medical Image Analysis
https://github.com/adgaudio/deepfixcx

deep-learning explainability image-compression privacy wavelet-packets

Last synced: 15 days ago
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DeepFix: Explainable Privacy-Preserving Image Compression for Medical Image Analysis

• Host: GitHub
• URL: https://github.com/adgaudio/deepfixcx
• Owner: adgaudio
• License: mit
• Created: 2021-10-04T15:23:55.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2023-03-11T13:08:44.000Z (over 1 year ago)
• Last Synced: 2024-10-03T11:12:05.251Z (about 1 month ago)
• Topics: deep-learning, explainability, image-compression, privacy, wavelet-packets
• Language: Python
• Homepage:
• Size: 32 MB
• Stars: 2
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# DeepFixCX : Explainable Privacy-Preserving Image Compression for Medical Image Analysis

Code accompanying the paper.

[Open Access Paper on Wiley WIREs Journal of Data Mining and Knowledge Discovery](https://doi.org/10.1002/widm.1495)











### Citation:

> Gaudio, A., Smailagic, A., Faloutsos, C., Mohan, S., Johnson, E., Liu, Y., Costa, P., & Campilho, A. (2023). DeepFixCX: Explainable privacy-preserving image compression for medical image analysis. WIREs Data Mining and Knowledge Discovery, e1495. https://doi.org/10.1002/widm.1495

        @article{deepfixcx,

            author = {Gaudio, Alex and Smailagic, Asim and Faloutsos, Christos and Mohan, Shreshta and Johnson, Elvin and Liu, Yuhao and Costa, Pedro and Campilho, Aurélio},

            title = {DeepFixCX: Explainable privacy-preserving image compression for medical image analysis},

            journal = {WIREs Data Mining and Knowledge Discovery},

            volume = {n/a},

            number = {n/a},

            pages = {e1495},

            keywords = {compression, deep networks, explainability, medical image analysis, privacy, wavelets},

            doi = {https://doi.org/10.1002/widm.1495},

            url = {https://wires.onlinelibrary.wiley.com/doi/abs/10.1002/widm.1495},

            eprint = {https://wires.onlinelibrary.wiley.com/doi/pdf/10.1002/widm.1495},

        }

### Reproducibility

All experiments are in `./bin/experiments.sh` and `./bin/experiments_extended.sh`

It's research quality code.  Please open a GitHub issue if there is a reproducibility

problem.  Note that the name was "DeepFix" and then we changed it to "DeepFixCX".

### Installation

```

# cd into the root of the repository.

# Install libraries

pip install -r requirements.txt

pip install .  # install deepfix if you want.

```

### Use the API

Comments are in the docstrings.

```

# DeepFixCX:  Compress and privatize images:

from deepfixcx.models import DeepFixCXImg2Img

# Wavelet Packet layer may be useful in projects:

from deepfixcx.models.wavelet_packet import WaveletPacket2d

# DeepFixCX: just the compression or reconstruction parts.

from deepfixcx.models import DeepFixCXCompression, DeepFixCXReconstruct

```