e-UDA: Efficient Unsupervised Domain Adaptation for Cross-Site Medical Image Segmentation. - Hongwei Li 004; Timo Loehr; Benedikt Wiestler; Jianguo Zhang 001; Bjoern H. Menze (CoRR, 2020)

FedCostWAvg: A New Averaging for Better Federated Learning. - Leon Mächler; Ivan Ezhov; Florian Kofler; Suprosanna Shit; Johannes C. Paetzold; Timo Loehr; Claus Zimmer; Benedikt Wiestler; Bjoern H. Menze (BrainLes@MICCAI (2), 2021)

FedCostWAvg: A new averaging for better Federated Learning. - Leon Mächler; Ivan Ezhov; Florian Kofler; Suprosanna Shit; Johannes C. Paetzold; Timo Loehr; Benedikt Wiestler; Bjoern H. Menze (CoRR, 2021)

Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: The ADAM challenge. - Kimberley M. Timmins; Irene C. van der Schaaf; Edwin Bennink; Ynte M. Ruigrok; Xingle An; Michael Baumgartner 001; Pascal Bourdon; Riccardo de Feo; Tommaso Di Noto; Florian Dubost; Augusto Fava-Sanches; Xue Feng 001; et al. (NeuroImage, 2021)

blob loss: Instance Imbalance Aware Loss Functions for Semantic Segmentation. - Florian Kofler; Suprosanna Shit; Ivan Ezhov; Lucas Fidon; Izabela Horvath; Rami Al-Maskari; Hongwei Bran Li; Harsharan Bhatia; Timo Loehr; Marie Piraud; Ali Ertürk; Jan Kirschke; et al. (IPMI, 2023)

Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images. - Chinmay Prabhakar; Hongwei Bran Li; Johannes C. Paetzold; Timo Loehr; Chen Niu; Mark Mühlau; Daniel Rueckert; Benedikt Wiestler; Bjoern H. Menze (MICCAI (8), 2023)