KEMAI - Research Training Group on Medical XAI

KEMAI Research Training Group GRK 3012/1
Hendrik Möller & Robert Graf, TU Munich

Abstract

We present recent advances in automatic image processing pipelines designed for large-scale cohort studies, focusing on applications in the NAKO (German National Cohort) and back pain research. We first highlight our work on Image2Image translation methods—including denoising diffusion models and Pix2Pix networks—that enable missing sequences, correct reconstruction errors in water-fat imaging (MAGO-SP), and perform MRI-to-CT translation for accurate bone segmentation. The second part will focus on segmentation, showcasing models such as SPINEPS and TotalVibeSegmentator and our approach to generating new ground truths for training. We then turn to the analysis of anomalies in the spine (e.g., variations in vertebral morphology, stump ribs, enumeration anomalies) and present initial findings on spine morphology and proton density fat fraction (PDFF) statistics across large population datasets.

Speaker Bios

Hendrik Möller is a doctorate student in computer science at the University Hospital rechts der Isar at TUM (Department for Diagnostic and Intervenrional Neuroradiology). He works in an EU-funded project around the NAKO (transl. national cohort) dataset, a large MRI cohort representing the german population. He develops machine learning methods to label and segment these scans with a practical orientation. Before that, he finished his Master’s in Robotics, Cognition, and Intelligence at the Technical University of Munich.

Robert Graf is a PhD student affiliated with the Institute of Artificial Intelligence in Medicine at the Technical University of Munich (TUM) and the Deep-Spine group. He works on Spine image translation, superresolution, registration, and analysis.

Time & Place

Wednesday, May 21, 2025
13:00 – 14:00
Building O27, Room 441

Download the full announcement (PDF)