Raidionics processing backend for performing segmentation and computation of standardized report (RADS)

The code corresponds to the Raidionics backend for running processing pipelines over MRI/CT scans. The segmentation of a few organs or tumor types, as well as the generation of standardized reports are included.
The module can either be used as a Python library, as CLI, or as Docker container.

Installation

pip install raidionicsrads
or
pip install git+https://github.com/dbouget/raidionics_rads_lib.git

Getting started

Notebooks

Below are Jupyter Notebooks including different examples on how to get started with the segmentation and reporting tasks, either over the brain or mediastinal area.

Notebook	Clinical target	Colab	GitHub
Preoperative Segmentation	:brain: Neuro
Preoperative Segmentation	:lungs: Mediastinum
Postoperative Segmentation	:brain: Neuro
Simple Reporting	:brain: Neuro
Surgical Reporting	:brain: Neuro
Batch processing	:brain: Neuro	-

raidionicsrads -c CONFIG (-v debug)

from raidionicsrads.compute import run_rads
run_rads(config_filename="/path/to/main_config.ini")

docker pull dbouget/raidionics-rads:v1.3-py39-cpu

docker run --entrypoint /bin/bash -v /home/<username>/<resources_path>:/workspace/resources -t -i --runtime=nvidia --network=host --ipc=host --user $(id -u) dbouget/raidionics-rads:v1.3-py39-cpu

docker run -v /home/<username>/<resources_path>:/workspace/resources -t -i --runtime=nvidia --network=host --ipc=host --user $(id -u) dbouget/raidionics-rads:v1.3-py39-cpu -c /workspace/resources/<path>/<to>/main_config.ini -v <verbose>

How to cite

If you are using Raidionics in your research, please cite the following references.

The final software including updated performance metrics for preoperative tumors and introducing postoperative tumor segmentation:

@article{bouget2023raidionics,
    author = {Bouget, David and Alsinan, Demah and Gaitan, Valeria and Holden Helland, Ragnhild and Pedersen, André and Solheim, Ole and Reinertsen, Ingerid},
    year = {2023},
    month = {09},
    pages = {},
    title = {Raidionics: an open software for pre-and postoperative central nervous system tumor segmentation and standardized reporting},
    volume = {13},
    journal = {Scientific Reports},
    doi = {10.1038/s41598-023-42048-7},
}

For the preliminary preoperative tumor segmentation validation and software features:

@article{bouget2022preoptumorseg,
    title={Preoperative Brain Tumor Imaging: Models and Software for Segmentation and Standardized Reporting},
    author={Bouget, David and Pedersen, André and Jakola, Asgeir S. and Kavouridis, Vasileios and Emblem, Kyrre E. and Eijgelaar, Roelant S. and Kommers, Ivar and Ardon, Hilko and Barkhof, Frederik and Bello, Lorenzo and Berger, Mitchel S. and Conti Nibali, Marco and Furtner, Julia and Hervey-Jumper, Shawn and Idema, Albert J. S. and Kiesel, Barbara and Kloet, Alfred and Mandonnet, Emmanuel and Müller, Domenique M. J. and Robe, Pierre A. and Rossi, Marco and Sciortino, Tommaso and Van den Brink, Wimar A. and Wagemakers, Michiel and Widhalm, Georg and Witte, Marnix G. and Zwinderman, Aeilko H. and De Witt Hamer, Philip C. and Solheim, Ole and Reinertsen, Ingerid},
    journal={Frontiers in Neurology},
    volume={13},
    year={2022},
    url={https://www.frontiersin.org/articles/10.3389/fneur.2022.932219},
    doi={10.3389/fneur.2022.932219},
    issn={1664-2295}
}