Challenge Dataset
A training dataset with processed SAX MR sequences of 145 subjects from clinical environment is used for model learning and validation. For each subject, 20 frames are included for the whole cardiac cycle. All ground truth values of the above-mentioned LV indices are provided for every single frame. More details about the training dataset can be found in the document of the DIG-Cardiac dataset. With the training dataset, we encourage the participants to report the performance of their algorithms with N-fold cross validation, where the following configuration are used : N=3, the number of each folds are (49, 48, 48);...
read moreEvaluation Criterion
Metrics Mean Absolute Error (MAE) and Pearson correlation coefficient (PCC) are used to assess the performance of the algorithms for estimation of areas, dimensions and regional wall thicknesses. For the 30 subjects in the test dataset, there are a total of 600 images. For any LV indices in {A1, A2, D1~D3, RWT1~RWT6}, the MAE and PCC can be computed as: where , is the groud truth value and is the estimated value, and are their mean values.
read morePaper Submission
Workshop paper All participants are encouraged to submit a full workshop paper describing their algorithms and results. Manuscript up to 8 pages should follow the template of main conferences’ paper and be submitted via the STACOM submission system.
read moreResults Submission
How Send algorithm output on the test dataset to organizers via email (lvquan18@outlook.com).
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