"The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient ..."

Akis Linardos et al. (2025)

> Home

Details and statistics

DOI: 10.48550/ARXIV.2512.06206

access: open

type: Informal or Other Publication

metadata version: 2026-01-23

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/corr/abs-2512-06206
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/corr/abs-2512-06206
Akis Linardos, Sarthak Pati, Ujjwal Baid, Brandon Edwards, Patrick Foley, Kevin Ta, Verena Chung, Micah Sheller, Muhammad Irfan Khan, Mojtaba Jafaritadi, Elina Kontio, Suleiman A. Khan, Leon Mächler, Ivan Ezhov, Suprosanna Shit, Johannes C. Paetzold, Gustav Grimberg, Manuel Nickel, David Naccache, Vasilis Siomos, Jonathan Passerat-Palmbach, Giacomo Tarroni, Daewoon Kim, Leonard L. Klausmann, Prashant Shah, Bjoern H. Menze, Dimitrios Makris, Spyridon Bakas:
The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods for Federated Learning. CoRR abs/2512.06206 (2025)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.