29.07.2025
©TUM
AI Research by Daniel Rückert Improves Medical Imaging and Data Privacy
TUM News
MCML Director Daniel Rückert and his team are developing AI technologies to improve diagnostic imaging and protect patient data. Their research includes federated learning approaches that allow models to learn from clinical data without sharing sensitive information, as well as privacy-enhancing techniques like added data noise.
Their methods are already being applied in MRI and CT systems, leading to shorter exam times and more accurate diagnostics. The work is a key step toward integrating trustworthy AI into daily clinical practice.
Related
28.11.2025
MCML at NeurIPS 2025
MCML researchers are represented with 45 papers at NeurIPS 2025 (36 Main, and 9 Workshops).
27.11.2025
Seeing the Bigger Picture – One Detail at a Time
FLAIR, introduced by Zeynep Akata’s group at CVPR 2025, brings fine-grained, text-guided detail recognition to vision-language models.
©BIFOLD/Michael Setzpfandt
25.11.2025
How Will Artificial Intelligence Redefine Medicine in the Next Decade?
AI in Medicine Workshop 2025 opened with strong momentum as experts from MCML and BIFOLD highlighted how AI will drive future healthcare innovation.
25.11.2025
Daniel Rückert Among the World’s Most Cited Researchers
MCML Director Daniel Rückert is among the world’s most cited researchers for AI in healthcare, part of 17 TUM scientists recognized in 2025.