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Deformable Dilated Faster-RCNN for Universal Lesion Detection in CT Images

Requirements

The following software needs to be installed on the system to setup the project:

  • GCC (version 5.0.0 or greater)
  • NVCC (Cuda Toolkit 10.2)
  • Python (version 3.7.x)

Setup

The following steps are required to setup the network:

  1. Install the required pip packages 
    pip install -r requirements.txt -f https://download.pytorch.org/whl/102/torch_stable.html
  2. Compile the program 
    python setup.py install develop
  3. Download and extract the relevant data for training (raw data is ~200GB + extracted data is ~21GB) 
    python __main__.py data_extraction
  4. Run the training, generate reports and previews 
    python __main__.py run

Features

Faster R-CNN

  • deformable convolution
  • deformable ROI pooling
  • deformable convolution and ROI pooling
  • dilated kernel using different rate values

License

MIT License

Copyright (c) 2021 Fabio Hellmann

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.