About
Dr. Thomas Pinetz is a researcher at the University of Bonn's Institute for Applied Mathematics, affiliated with the Effland Group. His work focuses on advancing medical imaging through deep learning, particularly in reducing contrast agent doses in MRI and enhancing image reconstruction techniques. He holds a PhD from Graz University of Technology, where his research centered on inverse problems in imaging using learning-based approaches and Wasserstein distances.
Prior to his current position, he collaborated with Prof. Alexander Effland in Graz, extending this research to medical applications. His expertise spans computer vision, machine learning, and medical imaging, addressing challenges like signal amplification in brain MRI and synthetic data generation for radiology.
His recent publications emphasize ethical concerns in AI generalizability, contrast agent reduction, and clinical applications such as stroke detection via CT-angiography. He actively contributes to open-source tools and collaborates across disciplines, bridging mathematics and life sciences.
Office: N 2.002, Endenicher Allee 60, Bonn. Contact: tpinetz@uni-bonn.de.
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