Fig. 1: Concept and main findings of the Federated Tumor Segmentation (FeTS) Challenge.

The FeTS challenge is an international competition to benchmark brain tumor segmentation algorithms, involving data contributors, participants, and organizers across the globe. Test data hubs are geographically distributed while training data is centralized. Participants include those from the 2021 and 2022 challenges. Task 1 focused on simulated federated learning and we consistently saw an increase in performance by teams utilizing variants of selective sampling in their federated aggregation. In Task 2, submissions are distributed among the test data hubs for evaluation. As a representative example, the top-ranked model shows good average segmentation performance (measured by the Dice Similarity coefficient, DSC) but also failures for individual cases. Cases with empty tumor regions and data sites with less than 40 cases are not shown in the strip plot. Source data are provided as a Source Data file.