Published May 1, 2022 | Version v1
Dataset Open

Cross-Modality Domain Adaptation Challenge 2022 (crossMoDA)

  • 1. King's College London, United Kingdom
  • 2. Elisabeth-TweeSteden Hospital, Tilburg, Netherlands

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.

Files

crossmoda2022_training.zip

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Additional details

Funding

Wellcome Trust
Wellcome Trust Centre for Surgical and Interventional Sciences 203145
Wellcome Trust
King's College London Medical Engineering Centre of Research Excellence 203148