olfactory bulb segmentation pipeline

This repository contains a Nipype wrapper for the olfactory bulb segmentation tool for T2 weighted images available at /Deep-MI/olf-bulb-segmentation.

If you use this wrapper please cite:

Estrada, Santiago, et al. "Automated olfactory bulb segmentation on high resolutional T2-weighted MRI." NeuroImage (2021). https://doi.org/10.1016/j.neuroimage.2021.118464

@article{estrada2021automated,
  title={Automated Olfactory Bulb Segmentation on High Resolutional T2-Weighted MRI},
  author={Estrada, Santiago and Lu, Ran and Diers, Kersten and Zeng, Weiyi and Ehses, Philipp and St{\"o}cker, Tony and Breteler, Monique MB and Reuter, Martin},
  journal={NeuroImage},
  pages={118464},
  year={2021},
  publisher={Elsevier}
}

Build docker image

nvidia-docker build -t ob_pipeline -f docker/Dockerfile .




## Or pull from docker hub

```bash
docker pull dznerheinlandstudie/rheinlandstudie:ob_pipeline

Run pipeline:

Using docker

The pipeline can be run with docker by running the container as follows:

 nvidia-docker run --rm -v /path/to/input_scans:/input \
                 -v /path/to/work_folder:/work \
                 -v /path/to/output:/output \
        dznerheinlandstudie/rheinlandstudie:ob_pipeline \
        run_ob_pipeline \
        -s /input \
        --subjects test_subject_01 \
        -w /work \
        -o /output \ 
        -p 4 -g 1 -gp 1 

The command line options are described briefly if the pipeline is started with only -h option.

Using Singulraity

The pipeline can be run with Singularity by running the singularity image as follows:

singularity build ob_pipeline.sif docker://dznerheinlandstudie/rheinlandstudie:ob_pipeline

When the singularit image is created, then it can be run as follows:

singularity run --nv -B /path/to/inputdata:/input \
                     -B /path/to/work:/work \
                     -B /path/to/output:/output \
            ob_pipeline.sif "export TFNUM_THREADS=2;export GOTO_NUM_THREADS=2;\
            run_ob_pipeline \ 
                      -s /input \
                      -w /work \
                      -o /output \ 
                      -p 4 -g 1 -gp 1"