LV Segmentation Challenge


One major challenge for developing a 4D segmentation algorithm is the lack of available large set of ground truth that are defined for the whole cardiac frames and slices. Initiated from the 2011 LV Segmentation Challenge that was held for the 2011 STACOM Workshop, we have started up a larger collaborative project to establish the ground truth or the consensus segmentation images for myocardium. The segmentation challenge is therefore set to open for new algorithms to participate. We aim to establish consensus segmentation images from a large set of data. We used modified STAPLE method to generate the consensus images from the contributing participants (raters).  However, before the consensus images can be robustly established, we need a lot of participants, which are semi or fully automated segmentation methods. The more people join this work, the better the consensus images. Everybody can participate in this work, particularly for students and researchers in the field of fully automatic segmentation of the heart.

The Data

Size 100 cases for training set
100 cases for validation set
Source randomly selected from DETERMINE cohort
Pathology myocardial infarction
Images Steady-State Free Precession MRI in short and long axis views
Contours binary mask images (only for training set)

How To Participate


Read carefully and agree on Terms & Conditions and CAP Data Use Agreement documents.


Upon approval, you can download directly the data.


Start working on the training dataset. You must only use the data for developing an semi or fully automated segmentation algorithm.


When ready, submit binary mask images from the validation dataset.


You will get results back in terms of performance metrics and you will also be able to download the consensus images from the validation dataset.

Submitted Methods