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Imaging and analysis play a central role in nearly all areas of modern medicine. The research group "Image Processing and Medical Imaging" (IPMI) is dedicated to developing machine learning methods and automatic information processing for medical imaging.

Our focuses include the extraction and analysis of image-based surrogate parameters (Imaging Biomarkers) for optimized diagnostics, treatment planning, and therapy response assessment. We aim for targeted optimization of imaging parameters, such as in computer and magnetic resonance imaging. Additionally, we focus on the development and testing of new imaging techniques and protocols. We collaborate closely with clinical partners at the UKE and external collaborators.

To successfully implement our key activities, we utilize and develop efficient and innovative artificial intelligence (AI) and machine learning methods. Our specific focus lies in approaches to self-supervised learning and efficient learning with minimal data and uncertain data annotations. Furthermore, we collaborate with the Departments of Diagnostic and Interventional Radiology and Neuroradiological Diagnostic and Intervention to establish a forward-looking AI ecosystem for UKE Radiology.