Moritz Rabe

Moritz Rabe is a Postdoctoral Researcher in the Department of Radiation Oncology at the LMU University Hospital, affiliated with the Faculty of Physics at Ludwig-Maximilians-Universität (LMU) Munich. His work bridges medical physics and clinical radiation oncology, focusing on the integration of advanced imaging and artificial intelligence into radiotherapy workflows.

Education:

• PhD in Physics, 2022, LMU Munich
• MSc in Physics (focus: Medical Physics), 2017, Heidelberg University

Research Interests: Moritz Rabe's research is centered on enhancing the precision and adaptability of radiotherapy through innovations in motion modelling, MRI-guided radiotherapy (MRgRT), and artificial intelligence. His work explores deep learning for auto-segmentation, real-time target tracking, and synthetic image generation. He investigates functional MRI for toxicity prediction and develops methods for dose accumulation and plan adaptation in both photon and proton therapy, particularly for lung and prostate cancers.

Publication Trends: His recent publications (2023–2025) demonstrate a strong focus on AI-driven solutions in MR-guided radiotherapy, including deep learning for segmentation and motion prediction, synthetic 4D-CT generation, and clinical implementation of low-field MR-linac imaging. A recurring theme is the use of longitudinal imaging and patient-specific modelling to improve treatment accuracy and outcomes.

Scientific Awards:

• Behnken-Berger Award (for PhD)
• Two 2023 articles selected as Editor's Choice

Advising and Grants: While no formal advisees are listed, Moritz Rabe is supported by the prestigious Munich Medical & Clinician Scientist Program (MCSP) of the LMU Medical Faculty (funding received in 2023). He collaborates closely with Prof. Guillaume Landry and Dr. Christopher Kurz, contributing to a dynamic research environment focused on image-guided and adaptive radiotherapy.

Labs and Teams: He is a key member of the MR Guided Radiation Therapy research group at LMU, working within a multidisciplinary team that includes physicists, clinicians, and data scientists. His research is conducted at the intersection of the Faculty of Physics and the Department of Radiation Oncology, leveraging the capabilities of the 0.35 T MR-linac for innovative radiotherapy research.