When Clinical Expertise Meets AI Innovation – With Michael Ingrisch

Artificial intelligence has enormous potential in radiology — but realizing it requires more than good algorithms.

Michael Ingrisch, Clinical Data Science Professor at LMU and MCML PI, shares how his team took a practical approach: identifying a key diagnostic challenge in PET CT imaging and inviting the broader AI community to help solve it.

Through an open machine learning competition, participants used real clinical data to train models for tumor segmentation. The results were tested on unseen data, with the winning solution demonstrating not just technical skill — but clinical relevance.

Ingrisch highlights the importance of interdisciplinary collaboration: without it, even the best models risk solving the wrong problems. His team is working to ensure the next generation of AI tools is not only cutting-edge — but aligned with the real needs of clinicians and patients.

This video is part of our MCML spotlight series on researchers driving AI forward through real-world impact.

The film was produced and edited by Nicole Huminski and Nikolai Huber.