Mareike Thies

Friedrich-Alexander-Universität Erlangen-Nürnberg

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About

Mareike Thies is a biomedical imaging and robotics researcher whose work sits at the intersection of computed tomography (CT), robotic systems, and medical navigation. Her research focuses primarily on advancing CT imaging through intelligent trajectory optimization and novel reconstruction algorithms, with particular application to robotic X-ray systems in both clinical and industrial settings. Thies made an early impact with her work on fiducial-free 2D/3D registration for robot-assisted femoroplasty (35 citations), offering a significant practical improvement to hip fracture prevention procedures by eliminating the need for invasive external X-ray markers. She has since become a leading contributor to the emerging field of robotic CT trajectory design, demonstrating in her highly cited 2021 paper (28 citations) how task-specific trajectory optimization can expand the capabilities of twin-robotic CT systems. Her subsequent work introduced learning-based approaches to this challenge, reducing the number of projections required without sacrificing image quality. Most recently, her DRACO framework advances differentiable reconstruction for arbitrary cone beam CT orbits, addressing long-standing computational bottlenecks in iterative imaging. Across her portfolio, Thies consistently bridges algorithmic innovation with real-world clinical utility, making her a notable emerging voice in medical imaging research.