Participation guidelines

The CuRIOUS 2019 Challenge will offer two different image registration tasks for two different surgical stages after craniotomy: before resection and after resection.

Taks 1: Register pre-operative MRI to iUS before tumor resection

Taks 2: Register iUS after tumor resection to iUS before tumor resection

The challenge solicits robust and efficient MRI-iUS and iUS-iUS registration approaches to help correct brain shift throughout the intervention.

A participating team can join either or both sub-tasks for the challenge.

A training multi-modality clinical datasets, with expert-labeled homologous anatomical landmarks, is already publicly available. Then a testing dataset will be distributed to the participants three weeks prior to the event, and the ranking based on the new dataset will be revealed during the challenge. During the event, the top teams will be invited to present their methods and results as oral presentations, and prizes will be awarded.

The CuRIOUS challenge requires all participating teams to submit a 4-page manuscript in LNCS format (same as the main MICCAI conference, with max 8 pages allowed) to describe their algorithms and report their results on the pre-released training dataset. All automatic and semi-automatic registration approaches are welcome. The methodology manuscripts will be published in the MICCAI post-conference proceedings.

Only participants who submit their manuscripts will receive the test dataset for the final contest, and only those who submit the test data results and present their methods at the CuRIOUS event will be considered for the prizes and included in the follow-up publications. This means that at least one member of each participating team must register for the CuRIOUS2019 MICCAI event.


Manuscript submission instruction

Please submit your manuscript via email to and in the body of the email, be sure to include the following:

  • Manuscript title
  • Corresponding author, affiliation, and email address
  • Manuscript abstract
  • Your team name

Please include your manuscript as a PDF document in the email, and make sure that the manuscript:

  • contains concise but sufficient description of your method
  • fully demonstrates the results of the training dataset (metric for each case)
  • includes the computational time and implementation details (software tools & hardware specs)
  • is in MICCAI format with 4-8 pages
  • is free of grammatical errors

The review process is not double-blind.

Evaluation metrics

The registration methods will be evaluated using the expert-labeled anatomical landmarks of the challenge datasets.

For each case:

  • The participants will submit the position of the transformed MRI landmarks or the iUS landmarks after registration.
  • The mean target registration errors (mTREs) will be computed between these landmarks and the ground truth ones defined in the before-resection iUS images.



  1. For each case and each participant team: compute the mean TREs on the landmarks.
  2. For each case, rank the teams according to the mean TREs.
    If two mTREs are less than 0.5mm different, the automatic method will be ranked higher.
    If a case has not been uploaded or could not be processed for some reason, the team will be ranked last for this case.
  3. Compute the mean rank of each team, which gives the final ranking of all participating teams.