If you'd like to participate in the final stage of our challenge, please download the respective test data and follow the task-specific instructions below:

  1. L2R 2022 Task 1 (NLST):
    * Download the test data and compute the displacement fields (same format as for validation). If you are unsure which cases to use, please see NLST dataset.json .
    * Upload your zip-compressed results no later than 09/06/2022 23:59 CET to this cloud storage . Please make sure to also include a txt-file containing your name, team, contact information and a short description/publication link of your algorithm. Your results are expected to reach about 3GB of size.
    * For a comparison of registration algorithms regarding inference time/runtime participants may submit their methods as docker containers (and thus, gain computation bonus points). All submitted docker containers will run on the same hardware. We provide a repo2docker example that you can extend or modify to prepare your submission https://github.com/MDL-UzL/L2R/tree/main/examples/submission/zerofield. If you'd rather use docker without repo2docker, you may do so. Please make sure to use bindings for the data path (/NLST/NLST_dataset.json) and the output path. We will be running the docker containers using CUDA Version 11.6.
    * The runtime of your algorithms will be computed for each registration pair by the time difference between the first access of the test data (fixed image, moving image, masks, etc.) and the moment the displacement field is written to disk. Keep this in mind when you are preparing your submission and avoid unnecessary computation (e.g. GPU initialization of you deep learning framework) during this time interval.
    * To avoid technical issues we kindly ask to also send an email to learn2reg@gmail.com containing the same information as mentioned above. We will confirm your submission has been uploaded successfully.

  2. L2R 2022 Task 2 (Continuation of previous tasks):
    * If you would like to submit to our previous tasks, please send us an email no later than 09/06/2022 23:59 CET to learn2reg@gmail.com . We will send you further instructions on how to upload your results.

  3. L2R 2022 Task 3 (Universial Registration Framework)
    * We have already reached out abour submission information to participants who qualified due to outstanding results in our snapshot evaluation. If you have not recieved any information but would still like to participate, please contact us.

You can find all information about this years' submission on our submission website

If you have any questions, please do not hesitate to contact us at learn2reg@gmail.com.