MICCAI 2026 CARDIAC IMAGING THEME  ·  JOINTLY WITH THE STACOM WORKSHOP

// Guidelines

Official Challenge Rules

To ensure a fair, transparent, and reproducible challenge, all participants must strictly adhere to the following rules. Failure to comply may result in disqualification.

1
Registration & Teams: All individuals wishing to participate must register on Synapse using their real name, complete affiliation details, and institutional email address. Incomplete profiles may be removed without notice. Each team is permitted to have a maximum of six members.
2
Submission Requirements & Paper Eligibility: To be eligible for test-set evaluation, leaderboard placement, and awards, teams must submit both:
  • A methodology paper (4–8 pages, LNCS format) submitted via the EchoRisk OpenReview venue by 1 July 2026. Papers should describe the method and validation-set results. Camera-ready versions (due 27 August 2026) may be updated to include final test-set results after Docker evaluation.
  • A self-contained Docker image submitted via Synapse by 1 August 2026. Test-set access will only be granted to teams with a valid, accepted paper submission.

This policy ensures scientific accountability and is consistent with major MICCAI challenges such as HECKTOR and BraTS. Teams that submit a Docker container without a valid paper will not appear on the official leaderboard and are not eligible for awards.

3
Publication Agreement: By participating, you agree that your submitted methodology paper may be made publicly available on the challenge website. Organizers reserve the right to use information provided by participants, including evaluation scores, predicted labels, and paper content, for the joint challenge summary publication.
4
Account Integrity: Participants are strictly prohibited from registering multiple teams or accounts. Creating alternative accounts to bypass submission limits will lead to immediate disqualification of all associated accounts.
5
Data Usage (DUA): Redistribution, sharing, or transfer of the CARDIOCARE challenge data or data links is strictly prohibited. Participants must use the data solely for their own model development within the context of this specific challenge.
6
Methods & External Data: Solutions must be fully automated during inference with no manual interventions (e.g., manual annotation of test cases). The use of public external datasets and pre-trained models (e.g., EchoNet-Dynamic, foundation models) is permitted, provided they are publicly available to all and explicitly disclosed in the methodology paper.

// Q&A

Frequently Asked Questions

Do I have to participate in all tasks?
No. You may choose to participate in Task 1, Task 2, Task 3, or any combination of them. Each task has its own independent leaderboard, evaluation, and prize pool.
Can I use external data or pretrained models?
Yes. You may use publicly available external datasets and pretrained weights (e.g. EchoNet, EchoPrime, ImageNet). Fine-tuning a public checkpoint on the challenge training data is also permitted. However, fine-tuning on a private or institutional dataset is not permitted — all external resources must be publicly available so that any team could in principle reproduce your pipeline. All external data and weights used must be explicitly disclosed in your methodology paper, including any additional fine-tuning performed and on what data.
Is a paper submission required to access the test set?
Yes. A valid methodology paper submitted via the EchoRisk OpenReview venue by 1 July 2026 is a prerequisite for test-set evaluation and leaderboard inclusion. This is a firm requirement, consistent with major MICCAI challenges such as HECKTOR and BraTS.

Papers submitted by 1 July should describe the method and validation-set results. The camera-ready version, due 27 August 2026, may be updated to include final test-set results after Docker evaluation closes on 20 August.
What are the computational resources for evaluation?
Submissions will be evaluated using one dedicated GPU (≥16 GB VRAM), multi-core CPU resources, and ≥32 GB of system memory. Final hardware specifications (exact GPU model, CPU configuration, RAM) will be announced no later than 3 months before the test submission deadline.

Each task is allocated a maximum wall-clock inference time of 15 minutes per task. Submissions that exceed this limit will be marked as failed for the affected task. Containers are evaluated on the largest case first; failure on the first case will terminate evaluation for that submission.

Note: All submissions must complete inference within the allocated resources. External API calls and internet access are strictly prohibited during inference.
Is there an online leaderboard during development?
No. Training and validation sets are released with ground-truth labels, allowing participants to conduct their own evaluation locally. Official rankings are determined solely by organiser evaluation of the hidden test set submissions.
Do we need to upload our training code?
No, we do not require teams to upload their training code. Only your inference code packaged as a self-contained Docker image is needed for challenge participation and final evaluation.
Are organizers allowed to participate?
Members of the organizer institutes are welcome to submit models and participate in the challenge for scientific benchmarking, but they are not eligible for monetary awards and will not be ranked on the public leaderboard.
Who should I contact with questions?
For any questions regarding registration, data access, or submission, contact the organising team at echorisk.miccai@gmail.com. We aim to respond within 3 working days.
What is the maximum number of team members allowed?
Each participating team can consist of up to a maximum of 6 people.
Can we preprocess the data?
Yes. During training, participants are allowed to perform standard data preprocessing. We do not restrict any data preprocessing techniques—we only evaluate your final model predictions.

Ready to participate?

Register on Synapse →

Questions? echorisk.miccai@gmail.com

CARDIOCARE
FORTH
UOI
HMU
NKUA
BOCOC
IEO
KSBC