Code for federated training of segmentation model

Code for federated training of a segmentation model through the federated learning framework FEDn

A 3D U-Net is trained through federated learning using the FEDn framework. An arbitrary number of clients is supported. Model performance can be monitored using Scaleout Studio.

The segmentation model expects four MR volumes per patient, and ground truth segmentations for brain tumor and brain stem. The code is written in Python.

Anyone working with federated learning or radiotherapy

See Github repository