Acdc article
The goal of this contest is 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).

While this challenge took place during the MICCAI 2017 conference, it remains open for new submissions over the next years.

This work has published to IEEE TMI journal. Please 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