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The Federated Tumor Segmentation (FeTS) and Open Federated Learning (OpenFL)

To enable distributed testing and training machine learning models without direct access to collaborator data, FeTS uses a technique called Federated Learning. The Open Federated Learning (OpenFL) framework is developed as part of a collaboration between Intel and the University of Pennsylvania (UPenn), as a part of Intel’s commitment in supporting the grant awarded to the Center for Biomedical Image Computing and Analytics at UPenn (PI: S.Bakas) from the Informatics Technology for Cancer Research (ITCR) program of the National Cancer Institute (NCI) of the National Institutes of Health (NIH), for the development of the Federated Tumor Segmentation (FeTS, www.fets.ai) platform (grant award number: U01-CA242871).

Disclaimer

• The software has been designed for research purposes only and has neither been reviewed nor approved for clinical use by the Food and Drug Administration (FDA) or by any other federal/state agency.
• Certain part of the code for this user interface (excluding dependent libraries) is governed by the license provided in https://www.med.upenn.edu/sbia/software-agreement.html unless otherwise specified.

For more details, please visit us at https://www.fets.ai/

For issues, please visit https://github.com/FETS-AI/Front-End/issues