Acdc article
The goal of this contest was two-fold:
  • compare the performance of automatic methods on the segmentation of the left ventricular endocardium and epicardium as the right ventricular endocardium for both end diastolic and end systolic phase instances;

  • compare the performance of automatic methods for the classification of the examinations in five classes (normal case, heart failure with infarction, dilated cardiomyopathy, hypertrophic cardiomyopathy, abnormal right ventricle).

This challenge took place during the MICCAI 2017 conference. It remained open until the end of 2022 for new submissions. The final leaderboard is given there.

This challenge is now closed. However, the data and the groundtruth are still publicly available via the following link.

You must refer to this citation for any use of the ACDC database.

  • O. Bernard, A. Lalande, C. Zotti, F. Cervenansky, et al.
    "Deep Learning Techniques for Automatic MRI Cardiac Multi-structures Segmentation and
    Diagnosis: Is the Problem Solved ?" in IEEE Transactions on Medical Imaging,
    vol. 37, no. 11, pp. 2514-2525, Nov. 2018

    doi: 10.1109/TMI.2018.2837502

illustration of the segmentation task in 3D MRI