Overview

CAMUS article
The goal of this project is to provide all the materials to the community to resolve the problem of echocardiographic image segmentation and volume estimation from 2D ultrasound sequences (both two and four-chamber views). To this aim, the following solutions were set-up
  • introduction of the largest publicly-available and fully-annotated dataset for 2D echocardiographic assessment (to our knowledge). The CAMUS dataset, containing 2D apical four-chamber and two-chamber view sequences acquired from 500 patients, is made available for download

  • deployement of a dedicated Girder online platform. This platform aims at assessing in a reproductible manner the performance of methods for the segmentation of cardiac structures (left ventricle endocardium and epicardium and left atrium borders) and the extraction of clinical indices (left ventricle volumes and ejection fraction).

The CAMUS online platform is now available and will be maintained and kept open as long as the data remains relevant for clinical research.

This work has published to IEEE TMI journal. Please refer to this citation for any use of the CAMUS database

  • S. Leclerc, E. Smistad, J. Pedrosa, A. Ostvik, et al.
    "Deep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography" in IEEE Transactions on Medical Imaging,
    early acces, 2019

    doi: 10.1109/TMI.2019.2900516

illustration of the segmentation task in 2D echocardiography