Can I publish papers using the data or evaluation results?

Yes, please follow the data usage agreement, i.e., CC BY NC ND. Also, please cite the following papers when you use the data for publications:
[1] Lei Li, Veronika A Zimmer, Julia A Schnabel, Xiahai Zhuang*: AtrialJSQnet: A New Framework for Joint Segmentation and Quantification of Left Atrium and Scars Incorporating Spatial and Shape Information, Medical Image Analysis, vol. 76, 102303, 2022. link.
[2] Lei Li, Veronika A Zimmer, Julia A Schnabel, Xiahai Zhuang*: Medical Image Analysis on Left Atrial LGE MRI for Atrial Fibrillation Studies: A Review, Medical Image Analysis, vol. 77, 102360, 2022. link.
[3] Lei Li, Veronika A Zimmer, Julia A Schnabel, Xiahai Zhuang*: AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-Center LGE MRIs, MICCAI, 557–566, 2021. link

Can I use semi-automatic segmentation algorithms in this challenge?

The challenge aims at both semi-automatic and fully-automatic segmentation methods. Two types of method will be ranked separately.

Can I participant in both tasks, i.e., "LA Scar Quantification" and "Left Atrial Segmentation from Multi-Center LGE MRIs"?

Yes，two tasks will be ranked separately. Also, we encourage new algorithms and publications on the joint segmentation and quantification, and the submitted algorithms will be evaluated on both of the two tracks (tasks) for ranking their performance.

Why some cases have pretty poor image quality (lots of motion artifacts)?

All the data were collected based on in vivo clinical environment and the data were used in clinics. So the data had various image quality, some data were with relative poor quality. However, it is necessary to include these datasets to validate the robustness of the developed algorithms when it comes to real clinical usage.

Can I use our own training data?

For fair comparison, participates are not allowed to use their own training data (either public or non-public).