Grundlagenforschung, KI und Translationale Forschung

AI-Assisted Healthcare

We are an interdisciplinary team of radiologists, computer scientists, and researchers who work closely together to develop AI solutions with a strong focus on clinical applicability.

Our research focuses on two main areas: image-based AI algorithms and text-based AI algorithms. In the area of image-based AI, we develop deep learning models for tasks such as segmentation, detection, and classification of pathologies on various medical imaging modalities.

In the area of text-based AI, we explore the potential of large language models for question answering, information extraction, text summarization, and workflow optimization in radiology.

We are committed to open science and reproducibility. We aim to make our datasets, code, and trained models publicly available whenever possible to foster collaboration and accelerate progress in the field.

Group Leaders
PD Dr. med. Lisa Adams
PD Dr. med. Lisa Adams
E-Mail +49 89 4140-1084
PD Dr. med. Keno Bressem
PD Dr. med. Keno Bressem
E-Mail https://github.com/kbressem
PD Dr. med. Sebastian Ziegelmayer
PD Dr. med. Sebastian Ziegelmayer
E-Mail
Group Members

Computer scientists

  • Anirudh Balaraman, M. Sc.
  • Zeineb Ben Chaaben, M. Sc. (PhD laufend an der TUM CIT: Prof. Dr. Julia Schnabel)
  • Fabian Drexel, M. Sc. (PhD laufend an der TUM CIT: Prof. Dr. Daniel Rückert)
  • Hartmut Häntze, M. Sc. (PhD laufend an der Radboudumc: Prof. Dr. Bram van Ginneken)
  • Jannik Lübberstedt, M. Sc. (PhD laufend an der TUM CIT: Prof. Dr. Christian Wachinger)
  • Johannes Moll, M. Sc. (PhD laufend an der TUM CIT: Prof. Dr. Daniel Rückert)
  • Friedrich Puttkammer, M. Sc. (PhD laufend an der TUM CIT: Prof. Dr. Christian Wachinger)
  • Andrei Zhukov, M. Sc.

Research associates and Physician scientists

  • Felix Dorfner
  • Dr. Marlene Fritzsche
  • Dr. Markus Graf
  • Dr. Anna Hinterberger
  • Dr. Su Hwan Kim
  • Miriam Kumpf, MD
  • Tristan Lemke, MD
  • Dr. Ina Luiken
  • Dr. Philipp Prucker
  • Dr. Lena Schmitzer
  • Era Stambollxhiu, MD
  • Lea Schumann, MD
  • Dr. Dominik Weller
  • Dr. Eva Wende

Doctoral and Bachelor students (ongoing)

  • Benjamin Berentelg
  • Melanie Eghbalian
  • Celine Dürner
  • Florian Gabriel
  • Raphael Huber
  • Finn Kosina
  • Falko Köhn
  • Simon Morin
  • Jimin Nam
  • Anna Schenck
  • Robert Staege
  • Maxima Warnick
  • Sadaf Zarrinkafsh
  • Christopher Zirn
Doctoral students (completed)
  • Dr. Behschad Bashian
  • Dr. Felix Busch
  • Dr. Leonhard Donle, M. Sc.
  • Dr. Günther Engel
  • Dr. Luise Franz
  • Dr. Gyeongphill Kang
  • Dr. Tristan Lemke
  • Dr. Jan Philipp Loyen
  • Dr. Jana Möckel, M. Sc.
  • Dr. Max Rattunde
  • Dr. Max Winter
  • Dr. Lina Xu
External Collaborators
  • Data Science and Text-based Information Systems (DATEXIS) (Berliner Hochschulte für Technik)
  • Department of Computing Science (Umeå University)
  • Department of Radiology (Charité, University Medical Center Berlin)
  • Department of Radiology (Università degli Studi di Salerno)
  • Department of Radiology (University Medical Center Aachen)
  • Department of Radiology (University Medical Center Freiburg)
  • Department of Radiology (University Medical Center Göttingen)
  • Diagnostic Image Analysis Group (Radboud Medical Center)
  • Faculty of Medicine and the Faculty of Computer Science (TUD Dresden University of Technology)
  • Harvard-MGB
  • Institute of Machine Learning in Biomedical Imaging (Helmholtz, Prof. Dr. Julia Schnabel)
  • Lab of Medical Physics and Digital Innovation (Aristotle University of Thessaloniki)
  • Lehrstuhl für Artificial Intelligence in Healthcare and Medicine (Prof. Daniel Rückert)
Grants and Awards
  • Else Kröner Exzellenzstipendium 2026 (Lisa Adams)
  • RSNA Honored Educator Award, 2025 (Lisa Adams, Keno Bressem)
  • Editor's Recognition Award for Radiology: Artificial Intelligence ('with special distinction'), 2025 (Lisa Adams, Keno Bressem)
  • Else Kröner Exzellenzstipendium 2025 (Keno Bressem)
  • Sachbeihilfe Deutsche Forschungsgemeinschaft 2025 (Lisa Adams)
  • Wilhelm Sander Projektförderung (Sebastian Ziegelmayer)
  • Wilhelm Sander Projektförderung (Lisa Adams, Keno Bressem)
  • Bayern Innovativ, OnkoBot, Grant, 2025 (Lisa Adams, Keno Bressem)
  • Bayern Innovativ, GO-TWIN, 2025 (Lisa Adams, Keno Bressem)
  • Walter Friedrich Prize of the German Radiological Society (DRG), 2024 (Keno Bressem)
  • Editor's Recognition Award for Radiology: Artificial Intelligence ('with special distinction'), 2024 (Lisa Adams)
  • Bayern Innovativ, InteRAGt, Grant, 2024 (Lisa Adams, Keno Bressem)
  • Digital Health Accelerator Funding (Phase I), Berlin Institute of Health, 2023 (Keno Bressem)
  • Walter Friedrich Prize of the German Radiological Society (DRG), 2023 (Lisa Adams)
  • EU Horizon (COMFORT Project), Funding by the European Union, 2023 (Lisa Adams, Keno Bressem (Consortium Lead))
  • Wilhelm-Sander-Stiftung, Grant, 2023 (Lisa Adams, Keno Bressem)
  • Gustav Bucky Prize, Radiological Society of Berlin, 2022 (Keno Bressem)
  • Feodor Lynen Research Fellowship, Humboldt Foundation, 2022 (Keno Bressem)
  • Research Fellowship, Max Kade Foundation Inc. New York | German Research Foundation, 2022 (Keno Bressem)
  • Funding Grant, German Society of Musculoskeletal Radiology, 2022 (Keno Bressem)
  • German Research Foundation (DFG) Collaborative Research Center 1340, Subproject Leader for Project B01, 2022 (Lisa Adams)
  • Alavi-Mandell Award, 2021 (Lisa Adams)
  • Digital Health Accelerator Funding (Phase I & II), Berlin Institute of Health, 2021 (Keno Bressem)
  • Digital Clinician Scientist Fellowship, Berlin Institute of Health, 2020 (Keno Bressem)
  • Clinician Scientist Fellowship from the Berlin Institute of Health, 2019 (Lisa Adams)
  • Junior Clinician Scientist Fellowship from the Berlin Institute of Health, 2017 (Lisa Adams)

 

Publications (selected)

Google Scholar Profil Lisa Adams

Google Scholar Profil Keno Bressem

  • Han, T.*, Adams, L. C.*, Bressem, K. K., Busch, F., Nebelung, S., & Truhn, D. (2024). Comparative Analysis of Multimodal Large Language Model Performance on Clinical Vignette Questions. JAMA. DOI: 10.1001/jama.2023.27861. *Shared first authorship.
  • Adams, L. C., Truhn, D., Busch, F., Kader, A., Niehues, S. M., Makowski, M. R., Bressem, K. K. (2023). Leveraging GPT-4 for post hoc transformation of free-text radiology reports into structured reporting: a multilingual feasibility study. Radiology. DOI: 10.1148/radiol.230725.
  • Suryadevara, V.*, Hajipour, M. J.*, Adams, L. C.*, Aissaoui, N. M., Rashidi, A., Kiru, L., Theruvath, A. J., Huang, C. H., Maruyama, M., Tsubosaka, M., Lyons, J. K., Wei, E.W., Roudi, R., Goodman, S.B., Daldrup-Link, H.-E. (2023). MegaPro, a clinically translatable nanoparticle for in vivo tracking of stem cell implants in pig cartilage defects. Theranostics. DOI: 10.7150/thno.82620. *Shared first authorship.
  • Bressem, K. K., Papaioannou, J. M., Grundmann, P., Borchert, F., Adams, L. C., Liu, L., Busch, F., Xu, L., Loyen, J. P., Niehues, S. M., Augustin, M., Grosser, L., Makowski, M. R., Aerts, H.J.W.L., Löser, A. (2024). Medbert. de: A comprehensive German BERT model for the medical domain. Expert Systems with Applications. DOI: 10.1016/j.eswa.2023.121598.
  • Busch, F., Xu, L., Sushko, D., Weidlich, M., Truhn, D., Müller-Franzes, G., Heimer, M. M., Niehues, S. M., Makowski, M. R., Hinsche, M., Vahldieck, J. L., Aerts, H.J.W.L, Adams, L.C.*, Bressem, K. K.* (2023). Dual center validation of deep learning for automated multi-label segmentation of thoracic anatomy in bedside chest radiographs. Computer Methods and Programs in Biomedicine. DOI: 10.1016/j.cmpb.2023.107505. *Shared senior authorship.
  • Bressem, K. K., Adams, L. C., Proft, F., Hermann, K. G. A., Diekhoff, T., Spiller, L., Niehues, S. M., Makowski, M. R., Hamm, B. Propotov M., Vahldieck, J. L. & Poddubnyy, D. (2022). Deep learning detects changes indicative of axial spondyloarthritis at MRI of sacroiliac joints. Radiology. DOI: 10.1148/radiol.212526.
  • Adams, L. C., Makowski, M. R., Engel, G., Rattunde, M., Busch, F., Asbach, P., Niehues S. M., Vinayahalingam S., Van Ginneken, B., Litjens, G., Bressem, K. K. (2022). Prostate158-An expert-annotated 3T MRI dataset and algorithm for prostate cancer detection. Computers in Biology and Medicine. DOI: 10.1016/j.compbiomed.2022.105817.
  • Makowski, M. R.*, Bressem, K. K.*, Franz, L., Kader, A., Niehues, S. M., Keller, S., Rueckert, D., Adams, L. C. (2021). De novo radiomics approach using image augmentation and features from T1 mapping to predict Gleason scores in prostate cancer. Investigative Radiology. DOI: 10.1097/RLI.0000000000000788. *Shared first authorship.
  • Niehues, S. M.*, Adams, L. C.*, Gaudin, R. A., Erxleben, C., Keller, S., Makowski, M. R., Vahldiek, J. L., Bressem, K. K. (2021). Deep-learning-based diagnosis of bedside chest X-ray in intensive care and emergency medicine. Investigative Radiology. DOI: 10.1097/RLI.0000000000000771. *Shared first authorship.
  • Bressem, K. K., Adams, L. C., Vahldiek, J. L., Erxleben, C., Poch, F., Lehmann, K. S., Hamm, B., Niehues, S. M. (2020). Subregion radiomics analysis to display necrosis after hepatic microwave ablation—a proof of concept study. Investigative Radiology. DOI: 10.1097/RLI.0000000000000653
  • Bressem, K. K., Adams, L. C., Gaudin, R. A., Tröltzsch, D., Hamm, B., Makowski, M. R., Schüle, C. Y., Vahldiek, Niehues, S. M. (2020). Highly accurate classification of chest radiographic reports using a deep learning natural language model pre-trained on 3.8 million text reports. Bioinformatics, DOI: 10.1093/bioinformatics/btaa668.