Mukoviszidose e. V. Funds DZL Early-Career Research Project on AI-Based MRI Analysis

Chronic rhinosinusitis, a persistent inflammation of the paranasal sinuses, occurs particularly frequently in patients with cystic fibrosis. MRI scans can provide valuable information for assessing rhinosinusitis, but their evaluation has so far been time-consuming and labour-intensive. An objective and time-efficient classification of the disease is crucial, both for clinical assessment and for optimizing patient care. This is where Dr. Hagen’s project comes in: his team is working on an AI-supported, automated analysis of MRI images to determine pathological changes in the paranasal sinuses. This project is made possible by funding from Mukoviszidose e.V. (19.956 Euro).

TLRC researchers collaborate on AI-supported image analysis

The “Image-based Diagnosis and Therapy Support” working group at the Institute for Medical Informatics (IMI), led by TLRC faculty members Dr. Urs Eisenmann and Prof. Dr. Petra Knaup-Gregori, has been successfully active in the DZL working group “Artificial Intelligence & Digital Tools” in recent years. In close collaboration with Heidelberg DZL scientists from Diagnostic and Interventional Radiology led by PD Dr. Lena Wucherpfennig and Prof. Mark O. Wielpütz (University Medicine Greifswald), as well as Prof. Olaf Sommerburg (Pediatric Pneumology and Allergology and Cystic Fibrosis Center), interdisciplinary research projects on AI-supported image analysis are being implemented.

“Our interdisciplinary team of clinicians and data scientists focuses on the development of machine learning methods and AI applications for the analysis of MRI image data in patients with chronic muco-obstructive lung diseases,” explains Dr. Hagen. “We believe that the ‘MrRhino’ project, funded by Mukoviszidose eV, is the logical next step in applying our methods to the upper respiratory tract.” Further information about the project and the funding provided by Mukoviszidose e.V. can be found here (in German).