Description
Official training and validation sets of crossMoDA 2022. All data will be made available online with a permissive non-commercial copyright-license (CC BY-NC-SA 4.0), allowing for data to be shared, distributed and improved upon. If you use the data, please cite: 1. Shapey, J., Kujawa, A., Dorent, R., Wang, G., Bisdas, S., Dimitriadis, A., Grishchuck, D., Paddick, I., Kitchen, N., Bradford, R., Saeed, S., Ourselin, S., & Vercauteren, T. (2021). Segmentation of Vestibular Schwannoma from Magnetic Resonance Imaging: An Open Annotated Dataset and Baseline Algorithm [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.9YTJ-5Q73 2. Dorent, R. et al (2022). CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation. ArXiv https://arxiv.org/abs/2201.02831 Acknowledgments: This challenge is supported by Wellcome Trust (203145Z/16/Z, 203148/Z/16/Z), EPSRC (NS/A000050/1,
NS/A000049/1) and ZonMw (project number: 10070012010006) funding. All the organizers will have access to the
test set if needed.
NS/A000049/1) and ZonMw (project number: 10070012010006) funding. All the organizers will have access to the
test set if needed.
| Date made available | 1 May 2022 |
|---|---|
| Publisher | Zenodo |
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