petermcgor/predict-phe repository overview

To use this Docker container for lung macaque segmentation, simply follow these steps:

1. Point to your input data by binding it to the /data/data_in directory using the -i flag, like this:

2. Bind a folder for the output masks to /data/data_out using the -o flag, for example:

3. Optionally, specify the number of threads to use with the -t flag:

Here's an example Docker command:

docker run --gpus device=0 --shm-size=20gb -v /path_to_images:/data/ -it petermcgor/predict-phe:0.0.7 -i /data/data_in -o /data/data_out -t 8

Make sure that the path_to_images folder contains a subfolder named "data_in" with data in Nifti format (.nii.gz) and another subfolder named "data_out" for the results if you prefer to follow the concrete example.