Federated Learning

Multi-centre evidence without moving clinical data — collaborative, privacy-preserving learning across hospitals.

Clinical data are scattered across hospitals and cannot simply be pooled. With federated learning we train and evaluate models across institutions while the data stay where they are — handling heterogeneous (non-IID) data, label scarcity, personalisation and fairness between sites. Through OMI and the Medical Informatics Initiative we bring these methods to remote AI inference across German university hospitals.

Key questions

How can hospitals train a shared model when their data are non-IID and cannot leave the premises?
How do we personalise a federated model for each site while keeping it fair to all?
How do we generate multi-centre clinical evidence without moving patient data?

Funded projects 12 filter all →

Funded · 2026 · MISTAI

MISTAI: Medical Intelligence & Skills Training in AI

Bilateral UKB–Dnipro State Medical University project, funded by the NRW Ministry of Culture and Science, building an AI pipeline and training programme in …

Ministry of Culture and Science of North Rhine-Westphalia

Medical Imaging Responsible AI Federated Learning

Symposium on AI in Medicine & Food Science

Funded · 2025

Symposium on AI in Medicine & Food Science

German Academic Exchange Service

Medical Imaging Responsible AI Federated Learning

Strategic Arab-German Network for Affordable and Democratized AI (SANAD)

Funded · 2025 · SANAD

Strategic Arab-German Network for Affordable and Democratized AI (SANAD)

DAAD Funded Project (2025-2025)

German Academic Exchange Service

Medical Imaging Responsible AI Federated Learning

Affordable AI and Collaborative Federated Learning for Global Healthcare (EEDA)

Funded · 2023 · EEDA

Affordable AI and Collaborative Federated Learning for Global Healthcare (EEDA)

DAAD Funded Project with Beirut Arab University, Lebanon (2023-2023)

German Academic Exchange Service

Medical Imaging Responsible AI Federated Learning

Federated foundation models for multi-center CT staging of pancreatic cancer

Research collaboration · 2023 – ongoing

Federated foundation models for multi-center CT staging of pancreatic cancer

This project addresses preoperative staging of pancreatic ductal adenocarcinoma (PDAC), where lymph node metastasis is a major prognostic factor but CT-based …

Charité – Universitätsmedizin Berlin

UMG Göttingen

University of Melbourne / Peter MacCallum Cancer Centre

Medical Imaging Federated Learning

Deep learning to estimate aging from chest imaging

Funded · 2023 – 2026

Deep learning to estimate aging from chest imaging

The 3-year DFG Funded project with UniKlinikum Freiburg (2023-2026)

German Research Foundation

Medical Imaging Responsible AI Federated Learning

Open Medical Inference (OMI)

Funded · 2023 – 2027 · OMI

Open Medical Inference (OMI)

BMBF Funded Project through Medical Informatics Initaitive (MII) consortia (2024-2028)

Federal Ministry of Research, Technology and Space (BMFTR)

Medical Imaging Federated Learning

Federated learning for musculoskeletal segmentation in CT

Research collaboration · 2022 – 2023

Federated learning for musculoskeletal segmentation in CT

This collaboration explored federated learning for musculoskeletal segmentation in CT imaging across institutions in Germany and Japan.

NAIST

Federated Learning Medical Imaging

FLamby: Federated learning benchmarks for realistic healthcare settings

Research collaboration · 2021 – 2022

FLamby: Federated learning benchmarks for realistic healthcare settings

A central bottleneck in federated learning research is the lack of realistic, multi-center benchmarks reflecting the heterogeneity of clinical data.

Owkin

EPFL

Inria

École Polytechnique · IP Paris

Federated Learning

BigPicture Project

Funded · 2021 – 2027 · BIGPICTURE

BigPicture Project

The 6-year EU-funded BIGPICTURE project will herald a new era in pathology

Innovative Medicines Initiative (EU / EFPIA)

Medical Imaging Responsible AI Federated Learning

FedDis: Federated disentangled representation learning for brain anomaly detection

Research collaboration · 2020 – 2022

FedDis: Federated disentangled representation learning for brain anomaly detection

This research line addressed one of the central methodological challenges in collaborative medical AI: how to learn clinically meaningful representations across …

Technical University of Munich

Imperial College London

Federated Learning Medical Imaging

Deep Federated Learning in Healthcare

Funded · 2020 – 2025

Deep Federated Learning in Healthcare

This 5 years Helmholtz funded project to advance the field with Federated Learning algorithms in Medicine (2020-2025)

Helmholtz Association

Medical Imaging Responsible AI Federated Learning

Publications 20 filter all →

PromptGate: Client-Adaptive Vision–Language Gating for Open-Set Federated Active Learning

Adea Nesturi, David D. Gaviria, Jiajun Zeng, Shadi Albarqouni

Medical Image Computing and Computer Assisted Intervention – MICCAI 2026, Lecture Notes in Computer Science, 2026

Conference CORE A26.5% acc. Medical Imaging Federated Learning

Publisher PDF BibTeX

Federated CT foundation models for multi-center detection of lymph node metastasis in pancreatic cancer

Parinishtha Bhalla, David D. Gaviria, Patrick Kupczyk, Ali Seif Amir Hosseini, Lena Conradi, Uli Fehrenbach, Matthaeus Felsenstein, Dou Ma, Alexander Semaan, Shadi Albarqouni

Scientific Reports, 2026

Journal Q1IF 4.9 Medical Imaging Federated Learning

Publisher BibTeX

Multi-center Collaboration for Improved Lymph Node Metastasis Detection in Pancreatic Ductal Adenocarcinoma

David D. Gaviria, Parinishtha Bhalla, Konstantin Schürheck, Patrick Kupczyk, Lena Conradi, Matthaeus Felsenstein, Belinda Lee, Peter Gibbs, Hyun Ko, Alexander Semaan, Shadi Albarqouni

Helmholtz AI Conference 2025 (HAICON25, poster), Karlsruhe, 2025

Abstract Medical Imaging Federated Learning Federated foundation models …

Bridging Regulatory Science and Medical Imaging Evaluation; and Distributed, Collaborative, and Federated Learning: First International Workshop, BRIDGE 2025, and 6th International Workshop, DeCaF 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23 and September 27, 2025, Proceedings

Ghada Zamzmi, Annika Reinke, Ravi Samala, Meirui Jiang, Xiaoxiao Li, Holger Roth, Mariia Sidulova, Thijs Kooi, Shadi Albarqouni, Spyridon Bakas, others

Springer Nature, 2025

Edited volume Medical Imaging Federated Learning

Robust Federated Learning Methodology for Automatic Chest X-Ray Diagnosis

Carlos Fernández Del Cerro, Mónica Abella, Manuel Desco, Shadi Albarqouni

Medical Imaging with Deep Learning, 2024

Conference Medical Imaging Responsible AI Federated Learning

Publisher BibTeX

Guest Editorial Special Issue on Federated Learning for Medical Imaging: Enabling Collaborative Development of Robust AI Models

Holger R Roth, Nicola Rieke, Shadi Albarqouni, Quanzheng Li

IEEE Transactions on Medical Imaging, 2023

Journal Q1IF 12.4 Medical Imaging Responsible AI Federated Learning Deep Federated Learning in …

Publisher PDF BibTeX

Federated disentangled representation learning for unsupervised brain anomaly detection

Cosmin Bercea, Benedikt Wiestler, Daniel Rueckert, Shadi Albarqouni

Nature Machine Intelligence, 2022

Journal Q1IF 23.9 Medical Imaging Federated Learning Deep Federated Learning in …

Publisher PDF URL BibTeX

Distributed, collaborative, and federated learning, and affordable AI and healthcare for resource diverse global health

Shadi Albarqouni, Spyridon Bakas, Sophia Bano, M. Jorge Cardoso, Bishesh Khanal, Bennett Landman, Xiaoxiao Li, Chen Qin, Islem Rekik, Nicola Rieke, Holger R. Roth, Debdoot Sheet, Daguang Xu

Lecture Notes in Computer Science. Cham: Springer Nature, 2022

Journal Responsible AI Federated Learning

Publisher BibTeX

FedNorm: Modality-Based Normalization in Federated Learning for Multi-Modal Liver Segmentation

Tobias Bernecker, Annette Peters, Christopher L Schlett, Fabian Bamberg, Fabian Theis, Daniel Rueckert, Jakob Weiß, Shadi Albarqouni

arXiv (Cornell University), 2022

Preprint Medical Imaging Federated Learning

Publisher PDF BibTeX

Flamby: Datasets and benchmarks for cross-silo federated learning in realistic healthcare settings

Jean Ogier Du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux

Advances in Neural Information Processing Systems, 2022

Journal CORE A*25.7% acc. Federated Learning Medical Imaging Deep Federated Learning in …

Publisher PDF Code BibTeX

Semi-Supervised Federated Peer Learning for Skin Lesion Classification

Tariq Bdair, Nassir Navab, Shadi Albarqouni

Machine Learning for Biomedical Imaging, 2022

Journal Medical Imaging Federated Learning

Publisher URL BibTeX

Domain Adaptation and Representation Transfer and Distributed and Collaborative Learning: Third MICCAI Workshop, DART 2021, and First MICCAI Workshop, FAIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021: Proceedings

Shadi Albarqouni

Springer, 2021

Edited volume Medical Imaging Responsible AI Federated Learning

All 20 publications →

Datasets 3

FLamby — Federated Learning Benchmark for Healthcare

Jan 2025FLamby — Federated Learning Benchmark for Healthcare

Musculoskeletal Photon-Counting CT Dataset

Jan 2025Musculoskeletal Photon-Counting CT Dataset

Pancreatic Ductal Adenocarcinoma Multi-Center CT Dataset

Jan 2025Pancreatic Ductal Adenocarcinoma Multi-Center CT Dataset

Code 5

PromptGate

Jun 2026PromptGate

PDAC-CTFM — Scientific Report Paper

Apr 2026PDAC-CTFM — Scientific Report Paper Jun 2022Federated Learning

FedDis-NMI — The source code of FedDis

Jun 2022FedDis-NMI — The source code of FedDis Apr 2016ROAM

Teaching 8

CoMI-L — Winter 2026/27

Oct 2026CoMI-L — Winter 2026/27

CoMI-L — Summer 2026

Apr 2026CoMI-L — Summer 2026

CoMI-S — Winter 2025/26

Oct 2025CoMI-S — Winter 2025/26

FLH — Summer 2021

Mar 2021FLH — Summer 2021

FLH — Winter 2020/21

Oct 2020FLH — Winter 2020/21

Computational Medical Imaging (Lab)

Jan 0001Computational Medical Imaging (Lab)

Computational Medical Imaging (Seminar)

Jan 0001Computational Medical Imaging (Seminar)

Federated Learning in Healthcare

Jan 0001Federated Learning in Healthcare

Community & events 42

Our Lab at MICCAI 2026 in Strasbourg

Sep 2026 · Strasbourg, FranceOur Lab at MICCAI 2026 in Strasbourg

Two Awards to Attend MICCAI 2026 in Strasbourg

Sep 2026 · Strasbourg, FranceTwo Awards to Attend MICCAI 2026 in Strasbourg

Invited Talk at Karman Conference on Innovations in non-invasive and computational imaging

Sep 2026 · Aachen, GermanyInvited Talk at Karman Conference on Innovations in non-invasive and computational imaging

Our first cohort of the BIGS block course on AI in Medicine

Apr 2026 · Bonn, GermanyOur first cohort of the BIGS block course on AI in Medicine

Three Oral Presentations at ISBI in London

Apr 2026 · London, United KingdomThree Oral Presentations at ISBI in London

Organzie the Symposium on AI in Medicine and Food Sciences

Dec 2025 · Bonn, GermanyOrganzie the Symposium on AI in Medicine and Food Sciences

Invited Keynote at the 12th International Conference on Intelligent Computing and Information Systems (ICICIS) in Cairo, Egypt

Nov 2025 · Cairo, EgyptInvited Keynote at the 12th International Conference on Intelligent Computing and Information Systems (ICICIS) in Cairo, Egypt

Contributed to the GLOHRA’s fact-finding mission to Brussels

Nov 2025 · Brussels, BelgiumContributed to the GLOHRA’s fact-finding mission to Brussels

Organzie the Summer School on Biomedical Imaging with Deep Learning (BiLD)

Sep 2025 · Tunis, TunisiaOrganzie the Summer School on Biomedical Imaging with Deep Learning (BiLD)

Participated at the AI for Good Global Summit in Geneva, Switzerland

Jul 2025 · Geneva, SwitzerlandParticipated at the AI for Good Global Summit in Geneva, Switzerland

Panelist at Applied Case Studies of AI in Health for WHO EMRO Workshop, Egypt

Jul 2025 · Cairo, EgyptPanelist at Applied Case Studies of AI in Health for WHO EMRO Workshop, Egypt

Invited Talk at the Andalusian Research Institute in Data Science and Computational Intelligence (DASCI), Spain

Jun 2025 · Andalusia, SpainInvited Talk at the Andalusian Research Institute in Data Science and Computational Intelligence (DASCI), Spain