Deep learning models for the manuscript Development and external validation of an MRI-based neural network for brain metastasis segmentation in the AURORA multicenter study
WARNING: This code base is no longer supported. It still works, but we recommended using BrainLes AURORA instead, which offers much more flexibility in a convenient PyPI package.
- Clone this repository:
git clone https://github.com/neuronflow/AURORA
- Go into the repository and install:
cd AURORA pip install -r requirements.txt
- CUDA 11.4+
- Python 3.10+
- GPU with at least 8GB of VRAM
further details in requirements.txt
run_inference.py: Example script for single inference.
Input: t1_file, t1c_file, t2_file, fla_file
All 4 input files must be nifti (nii.gz) files containing 3D MRIs. Please ensure that all input images are correctly preprocessed (skullstripped, co-registered, registered on SRI-24, you can use BraTS Toolkit for that).
Output: segmentation_file
Add path to your desired output folder.
optional Output: whole_network_outputs_file, enhancing_network_outputs_file
when using the software please cite https://www.sciencedirect.com/science/article/pii/S0167814022045625
@article{buchner2022development,
title={Development and external validation of an MRI-based neural network for brain metastasis segmentation in the AURORA multicenter study},
author={Buchner, Josef A and Kofler, Florian and Etzel, Lucas and Mayinger, Michael and Christ, Sebastian M and Brunner, Thomas B and Wittig, Andrea and Menze, Bj{\"o}rn and Zimmer, Claus and Meyer, Bernhard and others},
journal={Radiotherapy and Oncology},
year={2022},
publisher={Elsevier}
}
This project is licensed under the terms of the GNU Affero General Public License v3.0.
Contact us regarding licensing.
If possible please open a GitHub issue here.
For inquiries not suitable for GitHub issues:
Florian Kofler florian.kofler [at] tum.de
Josef Buchner j.buchner [at] tum.de