xiaochengcike / brats-orchestra

BraTS ensemble code based on the Docker images used in the BraTS Challenge 2018

brats-orchestra

BraTS ensemble code based on the Docker images used in the BraTS Challenge 2018

Author: Christoph Berger

Version: 0.1

This code was part of my Bachelor`s thesis submitted at the Technical University of Munich in October 2018. The version published here is in the process of being adapted and built into a more general purpose segmentation pipeline to support more inputs and greater modularity.

This code makes use of containers taken from the BraTS Algorithmic repository, which can be found here: https://github.com/BraTS/Instructions/

Further info regarding the BraTS challenge (rules, how to particpate, publications) can be found at the official homepage: https://www.med.upenn.edu/sbia/brats2018.html

Some of the fusion results are pre-published in this summarizing manuscript: https://arxiv.org/abs/1811.02629 Please contact me if you intend to use parts of this work for your research, we'd be thrilled to hear about it.

Current functionality:

• segment.py is the front-end script to manage Docker containers for segmentation tasks and organises files to work with the containers
• fusion/fusion.py uses the resulting individual fusions to create a final result (using various methods)
• util/ contains various scripts to manage files on the filesystem, calculate metrics for segmentation performance, load and store medical images and more

Usage of segment.py

python3 segment.py /brats/dir/path/

/brats/dir/path/ is the path where all subject folders are located, which must look like this:

• /brats/dir/path/
  • pat123/
    • flair.nii.gz
    • t1.nii.gz
    • t2.nii.gz
    • t1c.nii.gz
  • pat456/
    • ...

And so on.. Resulting segmentations will be placed into pat123/pat123_<algorithm>_results/tumor_<algorithm>_class.nii.gz

Requirements

You need to have a working installation of Docker running on your system. Also, install all other required packages for this code to run using:

pip install -r requirements.txt

Current Tasks

• rebuild the configuration file system to use JSON and simplify I/O
• compatibility for automated GPU segmentation using Nvidia-Docker