Example docker container for the LNQ Challenge organized as part of MICCAI 2023.
Dockerfile
contains all the information used to create the Docker container.
Speficically, it uses the continuumio/miniconda
image and installs additionnal Python libraries. Then, it automatically executes a dummy algorithm src/run_inference.py
on all the scans located in /input/
and write the results in /output/
.
To build the docker image:
docker build -f Dockerfile -t [your image]
Containers submitted to the challenge will be run with the following commands:
docker run --rm -v [input directory]:/input/:ro -v [output directory]:/output -it [your image]
This repository is based on the intructions provided for the MICCAI WMH segmentation challenge 2017.