Albarqouni Lab — Computational Medical Imaging Research (CoMI), University of Bonn

Collective Intelligence for Inclusive Medical AI

We build medical-imaging AI that is reliable enough for the clinic, learns across hospitals without moving patient data, and works where resources are scarce — across three interconnected themes: Computational Medical Imaging, Affordable & Responsible AI and Federated Learning. At the University of Bonn & University Hospital Bonn.

Explore our researchJoin the lab →
172
publications
20,826
citations · h-index 45
42
projects · 12 active
59
partners · 29 countries

Research themes

All themes →
Computational Medical Imaging Medical foundation models, multimodal imaging and uncertainty — methods that turn images into reliable clinical evidence. 161 papers 34 projects 55 courses 26 resources Affordable & Responsible AI Fairness and robustness across populations and resource settings — AI that is affordable, trustworthy and works for everyone. 60 papers 25 projects 6 courses 10 resources Federated Learning Multi-centre evidence without moving clinical data — collaborative, privacy-preserving learning across hospitals. 24 papers 11 projects 8 courses 8 resources

Latest news & media

All media coverage →
Dec 2026 · University Hospital Bonn, GermanyMISTAI Computational Pathology Workshop Invited Talk at the ML4H Clinical AI Seminar Series, Broad Institute of MIT and Harvard Nov 2026 · Cambridge, MA, USA (virtual)Invited Talk at the ML4H Clinical AI Seminar Series, Broad Institute of MIT and Harvard Al-Quds newspaper on the Düsseldorf conference of the Friends of Al-Quds University in Germany (02.11.2026)Photo: Al-Quds Nov 2026Al-Quds newspaper on the Düsseldorf conference of the Friends of Al-Quds University in Germany (02.11.2026) Keynote and Panel Discussion at the Annual Conference of the Friends of Al-Quds University in Germany Oct 2026 · Düsseldorf, GermanyKeynote and Panel Discussion at the Annual Conference of the Friends of Al-Quds University in Germany Keynote at the An-Najah 1st Conference for AI Applications: Imagine the Future of AI in Medicine Oct 2026 · Nablus, Palestine (virtual)Keynote at the An-Najah 1st Conference for AI Applications: Imagine the Future of AI in Medicine Keynote on Resilience and Higher Education in Gaza at the DAAD Regional Office Cairo Oct 2026 · Cairo, EgyptKeynote on Resilience and Higher Education in Gaza at the DAAD Regional Office Cairo Medical Pitch Contest Bonn Oct 2026 · Bonn, GermanyMedical Pitch Contest Bonn Invited Lecture and Panel at the 3rd Arab Science Symposium in Germany (ASSG 2026) in Cologne Oct 2026 · Cologne, GermanyInvited Lecture and Panel at the 3rd Arab Science Symposium in Germany (ASSG 2026) in Cologne

Active projects

All projects →

Featured publications

JACR · 2026 Reducing Clinician Annotation Fatigue in Open-Set Federated Learning: A Client-Adaptive Vision-Language Gatekeeper Q1IF 5.3 IEEE TMI · 2023 Guest Editorial Special Issue on Federated Learning for Medical Imaging: Enabling Collaborative Development of Robust AI Models Q1IF 12.4 Nature Mach. Intell. · 2022 Federated disentangled representation learning for unsupervised brain anomaly detection Q1IF 23.9 Medical Image Analysis · 2026 When multi-institutional dataset aggregation masks shortcut-like behavior in Foundation Models for medical imaging Q1IF 11.8 Scientific Reports · 2026 Federated CT foundation models for multi-center detection of lymph node metastasis in pancreatic cancer Q1IF 4.9 The BMJ · 2025 FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare Q1IF 42.7

Recent publications

All publications →

Histopathologische Klassifikation konjunktivaler melanozytärer intraepithelialer Läsionen (CMIL) mit einem Deep-Learning-Algorithmus

Luna Toma, Mert Ikinci, Leticia Ussem, L. Bulirsch, A. Gulbins, Daniela Süsskind, Julia M Weller, Ashkan Shakarami, Karin U Loeffler, Frank G. Holz, Shadi Albarqouni, Martina Herwig-Carl

124th DOG Congress (Deutsche Ophthalmologische Gesellschaft), Berlin, 24–27 September 2026, 2026

Abstract PathologyOphthalmology INTERACT-CMIL: Interpretable …
DOG Congress

We are hiring

3 open positions — join us in Bonn.

See open positions →