Calibrated uncertainty in clinical language models: training models to express what they do not know, so a system can defer instead of answering confidently and wrongly (Rewarding Doubt, ICLR 2026; ConRad, MICCAI 2026)
Clinical reasoning agents that choose what to examine next: diagnosis as a sequential decision process in which the model requests the next informative examination before committing, trained with reinforcement learning (LA-CDM, ICLR 2026)
Structured, verifiable radiology reporting: generating and evaluating findings against a clinically grounded schema rather than a text-similarity score, so errors are measured where they matter clinically (RaDialog, Rad-ReStruct, FlexR)
Interpretable diagnosis from medical images: concept-level explanations a radiologist can check, and counterfactuals that show what would have changed the prediction (Xplainer, DIVA, diffusion autoencoders)
Longitudinal patient modelling and clinical world models: integrating prior imaging, earlier reports and clinical context across a disease course, and simulating how that course responds to treatment, so therapy decisions can be optimised over the whole trajectory (EHR2Path, TMLR 2026)
Curriculum vitae
Matthias Keicher leads theVision-Language Group at the Chair for Computer Aided Medical Procedures and manages the Interdisciplinary Research Lab (IFL) at Klinikum rechts der Isar in Munich since 2023. His group builds clinical decision support that reasons over imaging, prior reports and patient context. Current work spans structured radiology reporting, calibrated uncertainty in clinical language models, and longitudinal modelling of disease courses, in close collaboration with the Departments of Radiology and Neuroradiology at Klinikum rechts der Isar.
12/2024 - current: Postdoc and Group Leader at the Chair for Computer Aided Medical Procedures
01/2025 - 03/2025: Visiting Researcher, Stanford University, School of Medicine; Multimodal foundation models for radiology with Akshay Chaudhari
09/2019 - 12/2024: PhD student at the Chair for Computer Aided Medical Procedures
02/2019 - 12/2024: Research Manager at the Chair for Computer Aided Medical Procedures
08/2016 - 12/2018: CTO and Managing Director of SurgicEye GmbH
Dosimetry, interventional radiology and radio-embolisation
05/2015 - 07/2016: Director of Business Development, SurgicEye GmbH
Kim, Su Hwan; Ziegelmayer, Sebastian; Busch, Felix; Mertens, Christian J; Keicher, Matthias; Adams, Lisa C; Bressem, Keno K; Braren, Rickmer; Makowski, Marcus R; Kirschke, Jan S; Hedderich, Dennis M; Wiestler, Benedikt: Exposing the fragility of LLM reasoning through bias-inducing prompts: evidence from BiasMedQA. 2 (1), 2026 mehr…
Pellegrini, Chantal; Özsoy, Ege; Gassert, Florian T; Marka, Alexander W; Strenzke, Maximilian; Keicher, Matthias; Makowski, Marcus R; Navab, Nassir: Enhancing radiology workflows through collaborative AI-assisted chest X-ray reporting using large vision-language models: a proof-of-concept study. 17 (1), 2026 mehr…
Riedel, Evamaria O; Schinz, David; Keicher, Matthias; Rühling, Sebastian; El Husseini, Malek; Pellegrini, Chantal; Baum, Thomas; Dieckmeyer, Michael; Malagutti, Luca; Seeger, Isabel; Walburga, Anna S; Wiestler, Benedikt; Sollmann, Nico; Löffler, Maximilian T; Wagner, Arthur; Kirschke, Jan S: Diagnostic accuracy of deep learning vs. human raters for detecting osteoporotic vertebral compression fractures in routine CT scans. 36 (10), 2026, 7556-7571 mehr…
2025
Kim, Su Hwan; Schramm, Severin; Adams, Lisa C; Braren, Rickmer; Bressem, Keno K; Keicher, Matthias; Platzek, Paul-Sören; Paprottka, Karolin Johanna; Zimmer, Claus; Hedderich, Dennis M; Wiestler, Benedikt: Benchmarking the diagnostic performance of open source LLMs in 1933 Eurorad case reports. 8 (1), 2025 mehr…
Hedderich, Dennis M.; Keicher, Matthias; Wiestler, Benedikt; Gruber, Martin J.; Burwinkel, Hendrik; Hinterwimmer, Florian; Czempiel, Tobias; Spiro, Judith E.; Pinto dos Santos, Daniel; Heim, Dominik; Zimmer, Claus; Rückert, Daniel; Kirschke, Jan S.; Navab, Nassir: AI for Doctors—A Course to Educate Medical Professionals in Artificial Intelligence for Medical Imaging. Healthcare 9 (10), 2021, 1278 mehr…
Hedderich, Dennis M; Keicher, Matthias; Wiestler, Benedikt; Gruber, Martin J; Burwinkel, Hendrik; Hinterwimmer, Florian; Czempiel, Tobias; Spiro, Judith E; Pinto Dos Santos, Daniel; Heim, Dominik; Zimmer, Claus; Rückert, Daniel; Kirschke, Jan S; Navab, Nassir: AI for Doctors-A Course to Educate Medical Professionals in Artificial Intelligence for Medical Imaging. 9 (10), 2021 mehr…
Zellner, Tobias; Burwinkel, Hendrik; Keicher, Matthias; Bani-Harouni, David; Navab, Nassir; Ahmadi, Seyed-Ahmad; Eyer, Florian: Decision support for toxin prediction using artificial intelligence. 59 (6), 2021, 541-541 mehr…
2020
Czempiel, Tobias; Paschali, Magdalini; Keicher, Matthias; Simson, Walter; Feussner, Hubertus; Kim, Seong Tae; Navab, Nassir: TeCNO: Surgical Phase Recognition with Multi-stage Temporal Convolutional Networks. In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. Springer International Publishing, 2020 mehr…
Elskhawy, Abdelrahman; Lisowska, Aneta; Keicher, Matthias; Henry, Joseph; Thomson, Paul; Navab, Nassir: Continual Class Incremental Learning for CT Thoracic Segmentation. In: Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning. Springer International Publishing, 2020 mehr…
2014
Okur, Asl?; Hennersperger, Christoph; Runyan, Brent; Gardiazaball, José; Keicher, Matthias; Paepke, Stefan; Wendler, Thomas; Navab, Nassir: FhSPECT-US guided needle biopsy of sentinel lymph nodes in the axilla: is it feasible? 17 (Pt 1), 2014, 577-84 mehr…
Student projects
Feel free to contact me if your interested in an IDP, a guided research or a thesis.
Running and past projects:
Type
Title
Student
Master thesis
Question-Driven Interactive & Automated Follow-Up Reporting of Oncology CT Scans with MLLMs (with Josua Decker and Thomas Wendler at UKA Radiology)
Mehdi Attia
Master thesis
Metric Development for Automatic Radiology Report Formalization (with Francisco Pinto at Jacobian)
Beti Tuntari
Internship
Extending X-Ray Reporting with LLMs to 3D CT Images
Sina Namazi
Master Thesis
Learning-Based Registration of Vertebral CT Scans for Monitoring Longitudinal Changes in Cancer Patients with Spine Metastasis (in collaboration with Harvard Medical School)
Malika Sanhinova
Master Thesis
GRIP: Graph-Image Contrastive Pre-Training For Chest X-ray Understanding
Mohammed Kamran
Master Thesis
Domain-specific Self-Supervised Pretraining for Vertebral Body Diagnosis
Infectious Disease Modeling for COVID-19 with Increased Spatial Resolution - Investigating Opportunities for Machine Learning and Community Mobility Data (in collaboration with Johns Hopkins University)
Philipp Nikutta
Bachelor Thesis
Cervical Spine Segmentation and 3D Printing for Improved Patient Treatment Planning